Description

Key Responsibilities

• Design, develop, and enhance an enterprise AI platform integrating multiple Large Language Models (LLMs).
• Architect and implement scalable AI solutions using modern Agentic AI frameworks and Retrieval-Augmented Generation (RAG) architectures.
• Build intelligent AI agents capable of reasoning, planning, tool execution, and workflow orchestration.
• Develop secure, scalable, and highly available cloud-native AI applications on AWS.
• Design and implement REST APIs and microservices to expose AI capabilities to enterprise applications.
• Integrate AI services with enterprise systems, databases, APIs, and third-party platforms.
• Deploy, monitor, and optimize AI workloads on AWS ensuring performance, scalability, security, and cost efficiency.
• Work closely with product owners and engineering teams to translate business requirements into technical solutions.
• Drive architecture reviews, code quality, CI/CD automation, and engineering best practices.
• Evaluate emerging LLMs, AI frameworks, and cloud services to continuously improve the AI platform.
• Mentor developers and provide technical leadership across AI initiatives.

Required Technical Skills

Generative AI

• Strong hands-on experience with OpenAI GPT, Anthropic Claude, Llama, Mistral, Amazon Nova, or similar foundation models.
• Experience building enterprise-grade LLM applications.
• Expertise in Retrieval-Augmented Generation (RAG).
• Prompt engineering, prompt optimization, embeddings, semantic search, and model evaluation.
• Experience integrating multiple LLM providers and managing model orchestration.

Agentic AI

Hands-on experience with one or more of:

• LangChain
• LangGraph
• CrewAI
• Microsoft Semantic Kernel
• AutoGen
• Amazon Bedrock Agents

Experience developing:

• Multi-agent workflows
• Tool calling
• Function calling
• Memory management
• Planning and reasoning agents

AWS Cloud

Strong hands-on experience with:

• Amazon Bedrock
• Amazon SageMaker
• AWS Lambda
• ECS/EKS
• API Gateway
• Step Functions
• Amazon S3
• DynamoDB
• Amazon OpenSearch
• Amazon Aurora
• CloudWatch
• IAM
• VPC
• EventBridge
• Secrets Manager

Experience with Infrastructure as Code (Terraform, AWS CDK, or CloudFormation) is highly desirable.

Programming

• Python (mandatory)
• FastAPI / Flask
• REST APIs
• Microservices
• Docker
• Kubernetes
• Git
• CI/CD pipelines

Databases & Search

Experience with:

• PostgreSQL
• DynamoDB
• OpenSearch
• Pinecone
• Weaviate
• Chroma
• FAISS
• Milvus

Preferred Qualifications

• Experience building AI products from concept to production.
• Strong understanding of LLMOps, MLOps, observability, and AI monitoring.
• Experience implementing AI guardrails, responsible AI, and enterprise security controls.
• Familiarity with event-driven and serverless architectures.
• Knowledge of authentication, authorization, and API security

Key Skills

Education

Bachelor's degree