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.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
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