Lead AI Solution Developer

Job Description

About the role:

Join STADA as a Lead AI Solution Developer to shape, deliver, and operate production-grade Generative AI solutions at scale. You will lead the full lifecyclefrom user experience (UX) and web application/UI design through LLM selection, model integration, backend services, and data pipelinesdelivering secure, compliant, and cost-optimized applications on Azure, Databricks, and (where relevant) Google Cloud / Vertex AI.

In this role, you will provide technical leadership across multiple initiatives, drive architecture and engineering standards, and mentor other developers. You will be a hands-on lead who guides delivery teams, ensures quality, and translates business needs into robust GenAI products that non-technical users can adopt confidently.

Job Responsibilities:

• Lead end-to-end delivery of GenAI applications across multiple workstreams: discovery, scoping, architecture, implementation, CI/CD, deployment, monitoring, and continuous improvement.
• Provide technical leadership and oversight for a team of AI application developers: coaching, mentoring, code reviews, pairing, and defining best practices.
• Own solution and platform architecture decisions for GenAI applications, including reference architectures, reusable components, and patterns (RAG, agentic workflows, tool use, evaluation).
• Drive UI/UX excellence for web-based AI applications, ensuring intuitive experiences for non-technical users (Streamlit and/or React), consistent design patterns, accessibility, and usability.
• Select and integrate LLMs/AI models using frameworks such as LangChain/ LangGraph and platforms including Azure AI Studio / AI Foundry & Google Vertex AI.
• Design and govern robust backend services and APIs (Python with FastAPI and/or Django), ensuring scalability, reliability, and maintainability.
• Build and standardize data pipelines and RAG connectors across structured and unstructured sources; ensure secure access, lineage, and performance.
• Establish automated testing, evaluation, and release quality gates (pytest, integration tests, model quality tests, regression suites), plus observability standards (logs, metrics, tracing).
• Define & track performance, cost, and reliability KPIs (latency, throughput, token/cost budgets, uptime); lead optimization initiatives and FinOps practices for GenAI.
• Technical documentation and operational readiness; lead incident response and postmortems to improve reliability.
• Partner with product owners, business stakeholders, security, and compliance to ensure solutions meet enterprise requirements (incl. pharma/GxP where applicable).

Key Competencies Required:

• Bachelors / Masters / PhD in Computer Science, Data Science or a related field.
• 6 to 10 years of experience, including 24+ years delivering GenAI or ML applications
• Expert Python skills and software engineering expertise (Git, design patterns, code reviews, CI/CD, clean architecture, secure coding).
• Strong experience with LLM tooling & orchestration (LangChain, LangGraph, Semantic Kernel) and RAG architectures; familiarity with agentic patterns is highly valued.
• Proven web application leadership across backend and frontend, with a track record of building quality user interfaces and guiding UI/UX decisions.
• Hands-on experience with Azure cloud-native services and enterprise deployments; familiarity with Databricks and/or GCP/Vertex AI is a strong plus.
• Experience with containerization and orchestration (Docker, Kubernetes) and production operations (monitoring, on-call readiness, SRE/DevOps practices).
• Excellent communication skills; ability to translate technical trade-offs into business outcomes

Preferred Skills:

• Experience with Databricks and Azure AI Foundry; experience with GCP and Vertex AI for agentic solutions.
• Experience with multi-agent frameworks (AutoGen, CrewAI) and evaluation frameworks for GenAI quality and safety.
• Experience with vector databases (e.g., Chroma, Milvus) and modern retrieval stacks.
• Exposure to pharma GxP environments and compliance expectations.
• Microsoft Azure and/or Google Cloud Platform Developer/Architect certification.

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