Manager - GenAI Full Stack Developer

About the role

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.

Responsibilities

• 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.

Requirements

• 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:
• 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.

Qualifications

• 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.
• Able 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.

Preferred

• 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.

Benefits

The team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities.

Schedule

The team culture is collaborative and encourages team members to take initiative and seek on-the-job learning opportunities.

Pay

A reasonable estimate of the current range is $151,470 to $218,025.