Manager - GenAI Full Stack Developer
Indexed description
Recruiting for this role ends on May 31st, 2026
Work you'll do
- Lead client discovery, requirements, and solution shaping; translate needs into architecture, technical specifications, delivery plans, and acceptance criteria.
- Design, build, and implement custom AI/GenAI solutions tailored to business workflows and risk considerations.
- Architect and optimize agentic AI systems (e.g., tool-using agents, multi-step orchestration, multi-agent patterns) and integrate with enterprise platforms.
- Lead end-to-end RAG implementations including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, orchestration, and evaluation.
- Drive GenAI model build activities (training, fine-tuning, validation), benchmarking, and continuous improvement of quality, safety, latency, and cost.
- Oversee model deployment and production operations (monitoring, observability, incident response, iteration).
- Lead development pods (planning, quality, delivery), including code/design reviews, mentoring, and engineering best practices.
- Collaborate with cross-functional stakeholders (product, data, security, risk/compliance) to deliver scalable, maintainable solutions.
- Evaluate emerging GenAI/agent frameworks and cloud services; prototype and recommend fit-for-purpose approaches.
Qualifications
Required:
- Bachelor's degree (or equivalent) in Computer Science, Engineering, Data Science, or a related field.
- 6+ years of relevant experience in software engineering/full stack development and delivering AI/ML or GenAI-enabled solutions.
- Experience leading teams and delivering client-facing solutions with clear ownership for quality and timelines.
- Required technical skills (must have):
- GenAI / NLP / Agentic AI
- Python programming
- Natural Language Processing (NLP)
- Agentic AI, including LangChain, LangGraph, and LlamaIndex
- RAG (Retrieval-Augmented Generation)
- Prompt engineering
- Vector databases (design/usage/integration)
- Model build + deployment
- GenAI model build: training, fine-tuning, validation
- Model deployment (serving patterns, monitoring, iteration)
- Containers (e.g., Docker)
- Data engineering + APIs
- ETL (extract, transform, load) and data engineering (pipelines, quality, preprocessing)
- FastAPI (or equivalent) to build backend services
- API development and integration (RESTful services)
- Full stack engineering
- JavaScript/TypeScript
- HTML/CSS plus SASS/LESS
- UI/UX design principles
- Front-end frameworks: React, Angular, or Vue
- Cloud AI/ML services across Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)
- Vertex AI experience
- You should reside within a commutable distance of your assigned office with the ability to commute daily, if required
- You can expect to co-locate on average 3 times a week with variations based on types of work/projects and client locations
- Ability to travel up to 50%, on average, based on the work you do and the clients/sectors you serve
- Limited immigration sponsorship may be available.
- Cloud certification (AWS, Azure, or GCP) and/or AI/ML certification.
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
- Familiarity with AI/GenAI ethics and governance frameworks and implementing controls in production.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
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