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AI, ML, & Data Engineering

ADVANCE SOFTWARE ENGINEERING

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Staff Engineer, AI-Driven Product Development Location: Remote EU, must be based in the EU already  About the Client A fast growing digital business with a large consumer base and a engineering team that has outgrown the way it currently works. Leadership has created a new function dedicated to changing how products get designed, built, tested and shipped, and this is the first engineering hire into it. Role Overview You will report directly to the CIO and help shape the function from the ground up. There is a mandate and a direction, but no spec. You will help write it. The goal is an engineering organisation where AI agents carry a real share of the work across design, QA, testing and product delivery, and where engineers, and the people around them, take on broader ownership and ship as product builders. This is a hands-on role. You will prototype quickly, work in the codebase, and unblock hard problems yourself, while also setting direction, running design reviews and making the case to leadership in plain language. Responsibilities Own the roadmap for introducing AI agents into the engineering workflow, from design through to release Build and roll out agentic QA and test automation to widen coverage and catch regressions earlier Put AI into the delivery pipeline itself: code review, testing and deployment gates in GitHub or GitLab Help engineers and adjacent roles move into broader product ownership, with the tooling and coaching to back it up Make pragmatic build-versus-buy calls on AI tooling, weighing cost, latency, data privacy and vendor risk Set standards for how AI-assisted systems are designed, tested, monitored and rolled back Work closely with engineering leadership, product and data to find where AI creates real business value Mentor senior and mid level engineers and raise the technical bar across the team Required Skills and Experience Staff or Principal level scope: you have set technical direction, not only delivered against it Proven experience using AI agents to change how an engineering team builds and ships, with measurable results you can talk through Experience getting engineers, including sceptical ones, to adopt new ways of working Strong hands-on engineering background in a statically typed language such as Scala, Kotlin, Java, Go or Rust Solid grounding in event-driven, distributed systems (Kafka or equivalent) and an understanding of how they fail Hands-on experience with Kubernetes and Docker in production Good judgement on build-versus-buy decisions for AI platforms and tooling Comfort working from a mandate rather than a spec, and working directly with a senior executive Professional-level English, written and spoken No Sponsorship for this position 

Job title: Senior Data Engineer Job type: Contract Contract Length: 12 months Rate: $60-70 per hour Role Location: United States The Company: US healthcare technology company that has spent the last decade building software for hospitals and their medical device suppliers. Their platform takes manual, paper heavy steps out of how products are sourced, tracked and paid for around surgical procedures. They have recently raised new capital to expand the team. Role & Responsibilities: They are investing in their data platform and need a Senior Data Engineer to take ownership of a Databricks-based analytics stack. You will join a small team with a lot of autonomy and visibility, turning platform data into trusted models, reporting and AI-assisted analytics for customers and internal teams. This is greenfield ownership of a modern stack. Key Responsibilities: Design and maintain a star-schema warehouse and lakehouse in Databricks Build and scale dbt pipelines, covering models, tests and source management Develop a semantic layer that serves both BI and AI-driven analytics Tune pipeline performance and control compute cost Own CI/CD for the data platform, including automated data-quality and dashboard validation and promotion from Dev to Staging to Production Bring in data from internal services and customer systems on AWS Work with product, operations and leadership to turn business questions into dependable data products Set data engineering standards and mentor teammates as the team grows Core Requirements 5+ years of data engineering experience Strong hands-on Databricks experience (Delta Lake, Spark/SQL, Unity Catalog or similar) Production dbt experience at scale Advanced SQL and Python Dimensional modelling and warehouse design (star schema) Experience with AWS data services CI/CD and testing practices for data pipelines Clear communicator who is comfortable owning work in a startup setting Preferred Experience Experience with BI or semantic layer tools such as Looker or similar Exposure to AI/LLM-driven analytics or natural-language querying Background in healthcare, medtech, supply chain or B2B SaaS Familiarity with HIPAA and healthcare data security Accessibility Statement: Read and apply for this role in the way that works for you by using our Recite Me assistive technology tool. Click the circle at the bottom right side of the screen and select your preferences. We make an active choice to be inclusive towards everyone every day.? Please let us know if you require any accessibility adjustments through the application or interview process. Our Commitment to Diversity, Equity, and Inclusion: Signify’s mission is to empower every person, regardless of their background or circumstances, with an equitable chance to achieve the careers they deserve. Building a diverse future, one placement at a time. Check out our DE&I page here

Lead Python AI Engineer – USA Location: USA Salary: $190000-210000 Working: Remote, with occasional client-site travel (few days every few months)   We are working with a leading AI engineering consultancy building an Agentic AI platform for a major global enterprise organisation.   As a Technical Lead, you will be responsible for leading and guiding development teams while working directly with clients to translate business and technical requirements into impactful applications.   This is a Forward Deployed Engineering position. You will work hands-on building an Agentic AI platform before working directly with customers to deploy and implement solutions within their environments.   The role is predominantly remote, with occasional travel to client sites across Europe. Typically, this will be around 3 days every couple of months, depending on project requirements. All travel and expenses are covered.   What we're looking for Strong commercial Python experience FastAPI experience is highly desirable Experience with cloud platforms and Kubernetes Strong platform / infrastructure understanding Comfortable working with AI coding tools such as Claude or Copilot Strong communication skills and confidence working directly with clients 2+ Years in leadership role (technical & people)   Interview process 30-minute talent call 1-hour live coding interview 45-minute conversational hiring manager interview   If you're a Lead Python engineer looking to work directly on the development and deployment of an Agentic AI platform, this is an opportunity worth exploring.

Product Manager – AI Platform (Contract) - Contract: 6–12 months minimum, extension possible - Location: 100% Remote (Mexico, Brazil, Argentina) - Hours: Full-time, US Central Time core hours, flexible around critical releases - Rate: $20 – $35 USD per hour  This is a remote contract for our US-based client. The contractor works from Mexico, Brazil or Argentina for a US team. The team works in English, so Professional Fluency in English (minimum) is required. About the Client An established US-based company providing billing, payroll and compliance technology to large enterprise customers. They are replacing an existing product with a new AI-native platform and need a product lead to take it from prototype to full production release. Role Overview You will own product for the new platform end to end, reporting to a senior executive. You'll shape the roadmap, close the gaps between prototype and launch, and keep product, delivery and engineering teams aligned. You'll also lead a small quality and compliance team and be the main day-to-day product contact for the engineers building the platform. Responsibilities - Own the product vision and a living roadmap with quarterly goals and monthly deliverables - Define MVP scope and priorities using impact and effort frameworks - Turn business outcomes into PRDs with user stories, flows and security, privacy and performance requirements - Maintain a single source of truth for requirements, acceptance criteria and change history - Work daily with an external engineering pod of four and internal engineering leads - Run backlog grooming, sprint planning and release readiness, cutting scope when needed - Validate API contracts and data mappings for integrations with payroll, staffing and finance systems - Hire and manage a QC Lead and two QC Engineers, and set the QA strategy, defect SLAs and go/no-go criteria - Plan migration, backfill and validation from the existing product's data model - Work with compliance specialists to build wage and labour compliance rules into the platform - Own auditability, including logs, lineage and reconciliation views for billing and compliance reporting - Define alpha, beta, MVP and GA criteria, coordinate phased cutovers, and prepare runbooks and training - Track post-launch KPIs and lead fast triage and stabilisation Required Skills and Experience - Proven product management experience taking a product from prototype to production - Experience writing PRDs, user stories and acceptance criteria - Hands-on experience managing engineering backlogs and sprints - Experience validating APIs and data mappings for system integrations - Experience leading or building QA/QC functions, including hiring - Comfort working with compliance-driven data, billing and reporting - Familiarity with Jira, Confluence, Figma, GitHub, Postman or Swagger, and Datadog or Grafana  

Job title: Scala Engineer Job type: Permanent Role Location: Remote - MUST be based in Portugal  The company: An international, mission-driven organisation using technology to improve access to essential services. The organisation operates across multiple markets and is growing its technology function to support a high-impact digital platform. Role and responsibilities: Develop and maintain backend services and new platform features. Design, test and improve secure, reliable and scalable software. Contribute to technical decisions and Agile ceremonies. Collaborate closely with engineers and wider teams. Produce clear technical documentation. Keep up to date with relevant technologies and engineering practices. Help maintain high standards around security, data protection and software quality. Job requirements: 4+ years of professional experience developing Scala backend systems, with functional programming knowledge Hands-on experience with the Typelevel ecosystem, ideally Cats/Cats Effect. Experience with microservices and AWS is highly desirable. Strong problem-solving and software engineering skills. Excellent written and spoken English. Benefits: Remote or flexible working arrangements. Location-specific benefits and allowances. Annual professional development budget. Generous/unlimited holiday policy. Opportunity to work on a growing, socially impactful product. High-trust, low-micromanagement working culture. Collaborative international team. Accessibility Statement:?  We make an active choice to be inclusive towards everyone every day.? Please let us know if you require any accessibility adjustments through the application or interview process.??  Our Commitment to Diversity, Equity, and Inclusion:  Signify’s mission is to empower every person, regardless of their background or?circumstances, with an equitable chance to achieve the careers?they deserve. Building a diverse future, one placement at a?time.??  Check out our DE&I page here  

Senior Business Analyst - Investments / Wealth / Capital Markets Location: Poland Signify Technology is partnering with a global technology consultancy to identify an experienced Senior Business Analyst for upcoming projects across investments, wealth management and capital markets. This opportunity would suit someone who combines strong financial services knowledge with the ability to turn complex business requirements into clear, practical solutions for technology teams. The role You’ll work closely with business stakeholders and delivery teams to understand requirements, assess existing processes and support the development of financial services platforms. Your responsibilities are expected to include: Leading requirements workshops with business and technology stakeholders. Translating business needs into functional requirements, user stories and acceptance criteria. Mapping processes and identifying opportunities for improvement. Working with engineers, architects and QA teams to clarify requirements throughout delivery. Supporting user acceptance testing and validating solutions against business needs. Communicating findings, priorities and delivery dependencies clearly. Your background We’re interested in speaking with candidates who bring: Strong experience as a Business Analyst within financial services. Relevant knowledge of investments, wealth management or capital markets. Experience delivering technology change within a bank, investment firm or financial services consultancy. Confidence managing stakeholders and leading requirements discussions. Strong analytical skills and the ability to explain complex concepts clearly. Experience working closely with software engineering teams. Strong written and spoken English. Experience with investment platforms, brokerage services or front-to-back investment processes would be particularly relevant. Why explore this opportunity? Contribute to technology projects within financial services. Work with international stakeholders and multidisciplinary delivery teams. Apply your domain expertise in a consultancy developing its business analysis and advisory capabilities. Accessibility Statement:?  We make an active choice to be inclusive towards everyone every day.? Please let us know if you require any accessibility adjustments through the application or interview process.??  ?  Our Commitment to Diversity, Equity, and Inclusion:  Signify’s mission is to empower every person, regardless of their background or?circumstances, with an equitable chance to achieve the careers?they deserve. Building a diverse future, one placement at a?time.?? 

Forward Deployed Engineer (Production LLM Systems) London, hybrid Permanent About the Client Our client is a well established UK business operating in a regulated sector, with a large customer base and a strong engineering culture. They are investing seriously in AI and are building a dedicated engineering team to take it from experiments into systems the business relies on every day.   The Role   Teams across the business have already started building their own AI tools, and this hire will give that work a safe route into production. You will work across three areas: Partnering with business teams to automate and improve how they work Taking models built by the in house ML team into live customer features Turning what you learn into shared tooling the whole company can use The focus is building dependable software that happens to use LLMs, so you will spend far more time on engineering than on prompts or model training.   What You Will Do Work directly with business teams to understand their problems, define the right solution, then design, build and deploy it Take projects from first prototype through to stable production, and agree clear ownership once they are live Build Python pipelines that combine deterministic steps with LLM calls, using good judgement on where each one belongs Put evaluation, guardrails, monitoring and cost controls around everything you ship Rebuild useful tools that teams have created for themselves into properly owned business systems when they prove their worth Deploy models built by the data science team into customer facing production, covering serving, integration and everything around the model Spot the patterns across your projects and turn them into shared tools and safe defaults that other teams can pick up and use themselves Learn from specialist engineers during the early stages of the team and help keep that knowledge in house What Success Looks Like   Early on, you will pick your first projects with the business, ship them, and be able to point to clear results. You will also help get one of the data science team's models running reliably for customers. What You Will Bring   Experience building for people outside engineering, whether as a consultant, a forward deployed engineer or on an internal platform team Comfort taking a vague problem and turning it into a scoped, deliverable system with minimal direction 5+ years of software engineering experience with real ownership of production systems A track record of building and shipping LLM based systems that have run in production Strong production Python as your main language Hands on experience working with models through APIs, including orchestration, structured output, tool use, agents and RAG where it fits Experience designing evaluation sets, measuring the accuracy of LLM steps, and regression testing prompts and workflows Practical safety experience, including PII handling, keeping data within the right boundaries, prompt injection awareness and human in the loop design Experience keeping LLM systems fast and affordable, whether through smarter model selection, caching or batching CI/CD, containerisation, and monitoring and alerting for AI workloads Solid data processing fundamentals, including pipelines, transformation, validation and handling anomalies

SOFTWARE ENGINEERING MANAGER Job Type: Full-time, Permanent Salary: $180,000–$220,000 + Equity Location: Onsite – Austin, Texas COMPANY OVERVIEW A Series A venture-backed fintech is building an operating system for a historically underserved market. The company serves both B2B operators and B2C consumers through a suite of integrated financial and operational products. Founded by experienced operators with prior startup success, the company is backed by top-tier fintech investors. The company just closed a $15M Series A and is experiencing rapid growth with strong market traction and an ambitious product roadmap centered on modern infrastructure and AI-native development. The company is entering a new phase of scaling and is expanding its engineering team to support increased demand from enterprise partners and individual users, with a focus on regulated product development and cutting-edge AI integration. ROLE OVERVIEW The Engineering Manager will lead a product engineering team of 4–8 engineers responsible for shipping core platform features. This is a hands-on leadership role requiring both strong management skills and continuous technical contribution. You'll work directly with product leadership and the founding team, with direct exposure to strategy and an opportunity to shape engineering culture, technical standards, and product direction during a critical scaling phase. LOCATION Candidates should be based in Austin, TX, as the product, engineering, and leadership teams operate locally in an in-office model. KEY RESPONSIBILITIES Lead and grow a product engineering team of 4–8 engineers, including hiring, performance management, and career development Stay hands-on: write code, review designs and implementations, make architectural decisions, and ship features alongside your team Own delivery end-to-end in partnership with your PM, translating product roadmap into shipped product Establish and maintain engineering standards: code review practices, testing strategy, documentation, observability Run team operations: design reviews, on-call rotations, incident response, standups, and post-mortems Develop engineers through regular 1:1s, performance feedback, and intentional career conversations Collaborate cross-functionally with product, design, and operations to align technical work with business needs IDEAL QUALIFICATIONS 7+ years of professional software engineering experience, including 2+ years managing engineers directly Strong backend-leaning full stack foundation in Ruby, React/Next.js, and TypeScript Demonstrated track record of growing and developing engineers from one level to the next Experience with third-party APIs, observability, on-call incident management, AWS, and Terraform Strong communicator who can represent engineering to non-technical stakeholders and navigate ambiguity Hands-on management philosophy — you should be writing and reviewing code regularly Experience in regulated fintech or compliance-heavy environments is a plus Familiarity with agentic AI, LLM applications, or modern AI development is a bonus Empathy for end users and a pragmatic approach to balancing shipping speed with engineering standards

Forward Deployed Engineer (Production LLM Systems) London, hybrid Permanent About the Client Our client is a well established UK business operating in a regulated sector, with a large customer base and a strong engineering culture. They are investing seriously in AI and are building a dedicated engineering team to take it from experiments into systems the business relies on every day.   The Role   Teams across the business have already started building their own AI tools, and this hire will give that work a safe route into production. You will work across three areas: Partnering with business teams to automate and improve how they work Taking models built by the in house ML team into live customer features Turning what you learn into shared tooling the whole company can use The focus is building dependable software that happens to use LLMs, so you will spend far more time on engineering than on prompts or model training.   What You Will Do Work directly with business teams to understand their problems, define the right solution, then design, build and deploy it Take projects from first prototype through to stable production, and agree clear ownership once they are live Build Python pipelines that combine deterministic steps with LLM calls, using good judgement on where each one belongs Put evaluation, guardrails, monitoring and cost controls around everything you ship Rebuild useful tools that teams have created for themselves into properly owned business systems when they prove their worth Deploy models built by the data science team into customer facing production, covering serving, integration and everything around the model Spot the patterns across your projects and turn them into shared tools and safe defaults that other teams can pick up and use themselves Learn from specialist engineers during the early stages of the team and help keep that knowledge in house What Success Looks Like   Early on, you will pick your first projects with the business, ship them, and be able to point to clear results. You will also help get one of the data science team's models running reliably for customers. What You Will Bring   Experience building for people outside engineering, whether as a consultant, a forward deployed engineer or on an internal platform team Comfort taking a vague problem and turning it into a scoped, deliverable system with minimal direction 5+ years of software engineering experience with real ownership of production systems A track record of building and shipping LLM based systems that have run in production Strong production Python as your main language Hands on experience working with models through APIs, including orchestration, structured output, tool use, agents and RAG where it fits Experience designing evaluation sets, measuring the accuracy of LLM steps, and regression testing prompts and workflows Practical safety experience, including PII handling, keeping data within the right boundaries, prompt injection awareness and human in the loop design Experience keeping LLM systems fast and affordable, whether through smarter model selection, caching or batching CI/CD, containerisation, and monitoring and alerting for AI workloads Solid data processing fundamentals, including pipelines, transformation, validation and handling anomalies  

AI Engineer Remote — LATAM | Brazil preferred | Contract-to-permanent Signify Technology is partnering with a fintech SaaS business looking for an AI Engineer to help build practical AI capabilities into its platform. This is an opportunity for someone who enjoys hands-on engineering, turning ideas into working products and collaborating with an international team. The role You’ll work closely with engineering and technical leadership to identify opportunities for AI, develop solutions and take them into production. Your responsibilities will include: Building and deploying AI features within an existing SaaS platform. Developing applications using large language models, including agentic workflows and retrieval-augmented generation (RAG). Connecting AI solutions with backend services, APIs and business data. Evaluating performance, reliability and the quality of AI outputs. Working with product and engineering colleagues to turn business requirements into practical solutions. What we’re looking for Strong software engineering skills, with hands-on Python experience. Experience building and deploying AI or LLM-powered applications. Familiarity with RAG, AI agents and integrating LLM APIs. Experience developing APIs and integrating applications with existing systems. An understanding of testing, monitoring and maintaining production software. Clear English communication skills and confidence working with an international team. Experience within fintech or B2B SaaS would be useful. Location and engagement Remote position for candidates based in LATAM, with Brazil preferred. Availability to collaborate during US working hours. Initial contract engagement, with the potential to move into a permanent position. Accessibility Statement:?  We make an active choice to be inclusive towards everyone every day.? Please let us know if you require any accessibility adjustments through the application or interview process.??  ?  Our Commitment to Diversity, Equity, and Inclusion:  Signify’s mission is to empower every person, regardless of their background or?circumstances, with an equitable chance to achieve the careers?they deserve. Building a diverse future, one placement at a?time.??