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.
