Technical Lead

Overview

We are looking for a Technical Lead to architect and develop production-quality Generative AI and Agentic AI applications using Python and cutting-edge frameworks like LangGraph and LangChain to manage multiagent workflows and orchestrate tool usage effectively.

Key Responsibilities

• Design and deliver end-to-end GenAI solutions with robust multiagent stateful workflows.
• Assess and configure foundational AI models including OpenAI, Anthropic, Azure OpenAI, Llama, Mistral, and Bedrock, focusing on prompt engineering, system prompting, function/tool integration, and tuning parameters such as temperature and context window size.
• Create advanced retrieval-augmented generation (RAG) pipelines using embedding techniques (OpenAI, Cohere, BGE), chunking strategies, vector databases (FAISS, Amazon OpenSearch, Pinecone), and ranking/evaluation methodologies.
• Develop agentic and workflow orchestration mechanisms implementing LangGraph graphs (message/state management, checkpoints), multi-step tools, human-in-the-loop processes, and LangChain agents with consistent input/output schemas.
• Build and manage datasets for evaluation, conduct offline and online assessments such as faithfulness, relevance, toxicity checks, and implement observability via MLflow, Weights & Biases, OpenTelemetry, LangSmith.
• Deploy secure and scalable solutions on AWS, utilizing Lambda, API Gateway, ECS/EKS, S3, SageMaker, DynamoDB, RDS, SQS/SNS, CloudWatch, IAM, and security controls like VPC and KMS.
• Engineer backend microservices with FastAPI or Flask, incorporating pagination, idempotency, caching, rate limiting, and typed contracts (pydantic) accompanied by comprehensive unit and integration testing.
• Lead DevOps and MLOps initiatives by managing infrastructure as code (Terraform/CDK), containerization via Docker, CI/CD pipelines with GitHub Actions, GitLab, or Jenkins, and orchestrate model rollouts with blue-green/canary deployments and feature flag management.
• Govern compliance and safety by enforcing controls on sensitive data, encryption, audit logging, content moderation, jailbreak mitigation, and documentation for models and data lineage.
• Collaborate cross-functionally with product, data, and security teams; conduct design and code reviews; mentor team members; manage technical debt; and establish best practices and playbooks to enhance performance measures such as latency, accuracy, cost, and adoption.

Qualifications

• Graduation degree (Any graduate eligible).