Sr Associate Software Engineer, AI Studio (Full Stack)

Roles & Responsibilities

• Define the component boundary with product, UX, business, domain, architecture and engineering partners; clarify intended use, acceptance criteria, non-functional requirements, user outcome, support expectations and estimates.
• Design and implement accessible, responsive UI components with clear state, secure sessions, loading, error, empty, streaming, review and approval patterns using modern JavaScript or TypeScript frameworks.
• Build APIs, services, background jobs, data models, queries, migrations, queues, events and integrations using Python, Node.js, Java or C#, SQL/NoSQL, versioned contracts, validation, authorization, retries and useful failure semantics.
• Integrate approved model inference, LLMs, embeddings, vector search, RAG, structured output, agent tools, BI or workflow automation with input/output validation, human control and component-level evaluation.
• Implement layered unit, integration, API, contract, UI, accessibility, performance, security, data and AI-evaluation tests and use evidence to diagnose moderate cross-layer failures.
• Use cloud services, containers, CI/CD, infrastructure as code where appropriate, feature flags, backward-compatible deployment, monitoring, rollback and incident practices.
• Define and maintain indicators for availability, latency, errors, frontend behaviour, database performance, data freshness, AI quality, user experience, operating cost and support health.
• Apply identity, least privilege, OWASP, privacy, Responsible AI, accessibility, validation, traceability and GxP controls; contribute reusable components and guide Associate engineers on familiar work.

Basic Qualifications and Experience

• Bachler’s/Master’s degree and 5 to 9 years of Computer Science, IT or related field experience.

Functional Skills

• Full-stack product engineering: Independent design, implementation, diagnosis and maintenance of a coherent frontend-to-backend production component or vertical slice.
• Backend, API, data and distributed systems: Versioned contracts, validation, authentication and authorization, caching, concurrency, queues, events, transactions, retries, idempotency, observability, persistence and schema evolution.
• AI-enabled applications and automation: Integration of predictive models, LLMs, embeddings, vector or hybrid search, RAG, structured output, tool-using agents, BI and deterministic workflows with human control.
• Testing, cloud and lifecycle reliability: Layered testing, source-control discipline, technical documentation, containers, CI/CD, configuration, versioning, monitoring, rollback, incident response, root-cause analysis and support.
• Security, Responsible AI and GxP: OAuth/OIDC, role-based access, least privilege, secrets, OWASP, privacy, threat awareness, prompt-injection safeguards, auditability, accessibility, validation and quality evidence.

Must-Have Skills

• Demonstrated ownership of at least one production frontend, backend, API, data, integration, automation or AI-enabled component.
• Strong hands-on proficiency in JavaScript or TypeScript, at least one backend language such as Python, Java, C# or Node.js, and SQL.
• Ability to design, build, release, monitor, diagnose and maintain a defined production slice with limited guidance.

Good-to-Have Skills

• Advanced frontend engineering: Experience with Next.js rendering patterns, reusable design systems, browser telemetry, frontend performance, complex data-intensive interfaces or accessible human-AI review workflows.
• Distributed services and integration: Experience with GraphQL, WebSocket, Kafka or other event platforms, durable workflows, outbox or saga patterns, stream processing, API gateways, graph/vector stores or complex integrations.
• AI and intelligent automation: Experience with scikit-learn, PyTorch, TensorFlow, Hugging Face, model-serving APIs, RAG evaluation, agent orchestration, document intelligence, computer vision, BI or automation.
• Cloud and observability: Experience with AWS, Databricks, Kubernetes, serverless services, infrastructure as code, OpenTelemetry, Prometheus, Grafana, Splunk, CloudWatch or feature management.
• Regulated delivery: Experience in healthcare, life sciences, GxP, validated systems or another regulated environment.

Soft Skills

• Independent ownership, sound technical judgment and disciplined production follow-through.
• Strong analytical and troubleshooting skills across frontend, API, data, integration and AI layers.
• Clear communication of design decisions, estimates, evidence, trade-offs, risks and support implications.
• Effective collaboration with product, UX, business, architecture, ML, platform, security, quality and operations teams.
• Ability to guide junior engineers and improve reusable engineering practices.

EQUAL OPPORTUNITY STATEMENT