Senior GenAI Engineer (7 Yrs)

Hiring: Data / GenAI Engineer (Contract – Remote)

Position Details

• Role: Data / GenAI Engineer
• Experience: 7–8+ Years
• Work Mode: Remote
• Shift: EST Time Zone (Approx. 5:30 PM/6:30 PM IST Start)
• Contract Duration: Initial Contract (Extendable up to 6–12 Months based on performance)

About the Role

We are seeking experienced Data/GenAI Engineers to join our Professional Services team and deliver enterprise-grade Generative AI solutions. The ideal candidate will have strong hands-on expertise in AWS, Amazon Bedrock, LLM integrations, Agent Frameworks, RAG architectures, and cloud-native application development.

You will work directly with global clients to build conversational AI assistants, document automation solutions, AI-powered analytics platforms, and production-ready GenAI applications.

Key Responsibilities

Generative AI & Application Development

• Design and develop production-ready GenAI applications using Amazon Bedrock and foundation models such as Claude, Nova, and Llama.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Develop AI Agents and multi-agent orchestration systems using LangChain, LlamaIndex, Bedrock Agents, or custom frameworks.
• Implement prompt engineering, few-shot learning, and fine-tuning strategies.
• Develop conversational AI solutions with context management and intent recognition.
• Integrate LLM APIs such as OpenAI, Anthropic Claude, and Cohere.

Cloud & Serverless Engineering

• Build serverless applications using AWS Lambda, API Gateway, Step Functions, and EventBridge.
• Develop scalable REST APIs and real-time AI interactions using FastAPI or Flask.
• Configure and optimize AWS services including S3, DynamoDB, RDS, SQS, SNS, and CloudWatch.
• Implement Infrastructure as Code using Terraform, CloudFormation, or AWS CDK.

Data Engineering & MLOps

• Design and develop data ingestion pipelines for structured and unstructured data.
• Create ETL/ELT workflows for data preparation and transformation.
• Implement vector embeddings and semantic search capabilities.
• Build data quality, observability, and monitoring frameworks.
• Optimize model performance, latency, scalability, and cost efficiency.

Client Engagement

• Participate in sprint planning, stand-ups, and client review sessions.
• Translate business requirements into technical solutions.
• Provide AI/ML best-practice recommendations to clients.
• Troubleshoot and resolve production issues efficiently.
• Maintain architecture, deployment, and operational documentation.

Mandatory Skills (Tier 1)

• Amazon Bedrock
• Generative AI & LLM Integration
• LangChain / LlamaIndex
• Python (3.9+) – Async Programming, Type Hints, Testing
• AWS Lambda & Serverless Architecture
• FastAPI / Flask
• Vector Databases (Pinecone, Weaviate, OpenSearch, Chroma, FAISS)
• Prompt Engineering
• RAG Architecture
• OpenAI / Anthropic Claude APIs

Preferred Skills (Tier 2)

• Amazon Bedrock AgentCore
• AWS API Gateway
• DynamoDB
• AWS Step Functions
• Docker, ECS, Fargate
• Pandas, PySpark, AWS Glue

Additional Skills (Tier 3 & 4)

• Embedding Models (Titan, OpenAI, Cohere)
• S3 & Data Lake Architecture
• CloudWatch Monitoring & Observability
• IAM & AWS Security
• CI/CD Pipelines (GitHub Actions, GitLab CI, CodePipeline)
• SageMaker
• OpenSearch
• EventBridge
• WebSockets
• AWS CDK
• Fine-Tuning & Model Training

Required Experience

• 7–8+ years of Software Engineering experience.
• 2–3+ years of AWS Production Experience.
• 1–2+ years of hands-on Generative AI experience.
• Proven experience delivering production-grade AI applications.
• Strong understanding of Agile/Scrum methodologies.
• Excellent communication and client-facing skills.