Data / Generative AI Engineers

Details:

• Contract Duration: Min 36 months
• Work Timing: 8:00 AM 4:00 PM EST
• Start Timeline: Within 2 weeks

Position Overview

We are seeking experienced Data/GenAI Engineers to join our Professional Services

team on a contract basis. You will work directly on client engagements delivering

production-grade Generative AI solutions, including conversational AI assistants,

document processing automation, RAG (Retrieval-Augmented Generation) systems,

and AI-powered data analytics platforms. This role requires hands-on technical

execution, client interaction, and the ability to work independently within an agile

delivery framework.

Primary Responsibilities

GenAI Solution Development

? Design and implement production-ready Generative AI applications using

Amazon Bedrock, Anthropic Claude, and other foundation models

? Build and optimize RAG (Retrieval-Augmented Generation) pipelines with vector

databases (Weaviate, OpenSearch, Pinecone)

? Develop AI agents and multi-agent orchestration systems using frameworks like

LangChain, LlamaIndex, or custom implementations

? Create conversational AI interfaces with natural language understanding, intent

detection, and context management

? Implement prompt engineering strategies, few-shot learning, and fine-tuning

approaches for domain-specific applications

AWS Cloud Architecture & Development

? Build serverless architectures using AWS Lambda, API Gateway, Step Functions,

and EventBridge

? Design and implement data pipelines for AI model training, inference, and

feedback loops

? Develop RESTful APIs and WebSocket connections for real-time AI interactions

? Configure and optimize AWS services including S3, DynamoDB, RDS, SQS,

SNS, and CloudWatch

? Implement infrastructure-as-code using CloudFormation, CDK, or Terraform

Data Engineering & ML Operations

? Design and build data ingestion pipelines for structured and unstructured data

sources

? Implement ETL/ELT workflows for data preparation, cleaning, and transformation

? Create vector embeddings and semantic search capabilities for knowledge

retrieval

? Develop data validation, quality monitoring, and observability frameworks

? Optimize model inference performance, latency, and cost efficiency

Client Engagement & Delivery

? Participate in sprint planning, daily standups, and client review sessions

plans

? Provide technical guidance and recommendations to clients on AI/ML best

practices

? Document architecture decisions, code, and deployment procedures

? Troubleshoot production issues and implement solutions quickly

Required Technical Skills (Priority Order)

Tier 1 - Critical Must-Haves

? Amazon Bedrock - Hands-on experience with foundation models (Claude, Nova,

Llama or others), model invocation, streaming responses, and guardrails

? Agent Frameworks & Orchestration - Production experience with LangChain,

LlamaIndex, Bedrock Agents, or custom multi-agent orchestration systems

? Python - Advanced proficiency with modern Python (3.9+), including async/await,

type hints, and testing frameworks (pytest, unittest)

? AWS Lambda & Serverless - Production experience building event-driven

architectures, function optimization, and cold start mitigation

? Vector Databases - Practical experience with at least one: Weaviate,

OpenSearch, Pinecone, Chroma, or FAISS for semantic search

? LLM Integration - Direct experience with LLM APIs (Anthropic, OpenAI, Cohere),

prompt engineering, and response parsing

? API Development - RESTful API design and implementation using FastAPI,

Flask, or similar frameworks

Tier 2 - Highly Valuable

? Amazon Bedrock AgentCore - Experience with AgentCore Runtime, Memory,

Gateway, and Observability for building production agent systems

? AWS API Gateway - Configuration, authorization, throttling, and integration with

Lambda/backend services

? DynamoDB - NoSQL data modeling, single-table design, GSI/LSI optimization,

and DynamoDB Streams

? AWS Step Functions - Workflow orchestration for complex AI pipelines and

multi-step processes

? Docker & Containers - Containerization, ECR, ECS/Fargate deployment for AI

workloads

? Data Processing - Experience with Pandas, PySpark, AWS Glue, or similar data

transformation tools

Tier 3 - Strong Differentiators

? RAG Architecture - End-to-end RAG system design including chunking

strategies, retrieval optimization, and context management

? Embedding Models - Working knowledge of text embeddings (Bedrock Titan,

OpenAI, Cohere) and embedding optimization

? AWS S3 & Data Lakes - S3 event notifications, lifecycle policies, and data lake

architecture patterns

? CloudWatch & Observability - Logging, metrics, alarms, and distributed tracing

for AI applications

? IAM & Security - AWS security best practices, least privilege access, secrets

management (Secrets Manager, Parameter Store)

? CI/CD Pipelines - Experience with CodePipeline, GitHub Actions, or GitLab CI for

automated deployments

Tier 4 - Nice to Have

? SageMaker - Model training, deployment, endpoints, and feature stores

? OpenSearch - Full-text search, vector search, and hybrid search implementations

? EventBridge - Event-driven architectures and cross-service integrations

? WebSockets - Real-time bidirectional communication for streaming AI responses

? AWS CDK - Infrastructure-as-code using Python or TypeScript CDK constructs

? Fine-tuning & Training - Experience with model fine-tuning, PEFT methods, or

custom model training

Required Experience & Qualifications

? 5+ years of software engineering experience with at least 2+ years focused on

AI/ML, data engineering, or cloud-native development

? 2+ years of hands-on AWS experience with production deployments

? 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)

? Proven track record delivering production AI applications from concept to

deployment

? Strong understanding of software engineering best practices (version control,

testing, code review, documentation)

? Experience working in agile/scrum environments with distributed teams

? Excellent problem-solving skills and ability to work independently with minimal

supervision

? Strong written and verbal communication skills for client-facing interactions

Preferred Qualifications

? AWS Certifications: Solutions Architect Associate/Professional, Machine

Learning Specialty, or Developer Associate

? Background in healthcare, financial services, or regulated industries with

understanding of compliance requirements (HIPAA, PCI-DSS, SOC 2)

? Contributions to open-source AI/ML projects or published technical content

? Experience with multi-tenant SaaS architectures and data isolation patterns

? Knowledge of cost optimization strategies for AI workloads (model selection,

caching, batching)

? Familiarity with frontend frameworks (React, Angular) for building AI-powered

UIs.

Project Examples You May Work On

? Building conversational AI assistants for customer service automation using

Bedrock and Anthropic Claude

? Implementing RAG systems for document processing, classification, and

intelligent search

? Developing AI-powered data extraction and validation pipelines for healthcare

claims processing

? Creating multi-agent systems for complex workflow automation and decision

support

? Building integration marketplaces connecting AI capabilities to third-party

platforms

? Designing voice AI solutions using Amazon Connect and Polly for customer

engagement

? Implementing AI-driven content recommendation and personalization engines.