Senior AI Engineer

At Staffworxs we dont just connect talent we power transformation. Headquartered in Frisco TX with teams in Bengaluru and Hyderabad we combine global reach with deep expertise. Our Digital & Data Analytics practice drives growth and innovation for some of the worlds top brands who continue to retain us as their trusted partner. If youre ready to make an impact youre in the right place.

Job Details:

Job Title: Senior AI Engineer
Location: Atlanta GA
Work Mode: 5 days onsite (Let me know if anybody asks for 3-4 days)
Duration: Long term Contract

Job Description
Experience

510 years overall 3 in GenAI/Agentic AI

Focus

Build conversational AI based product on AWS

Location

Atlanta GA (USA)

About the role
You will work closely with a client team in Atlanta to build a conversational AI product on AWS in a fast-paced environment. You own major components end to end turn the architecture into production-quality code and help the team move from concept to a production-ready release on an accelerated timeline. You are comfortable demoing to client stakeholders and leading technical work for less experienced engineers.

What you will do

• Build the core of the product conversational AI RAG and agents on AWS Bedrock/Bedrock AgentCore working closely with the AI Architect.
• Implement chatbot features: multi-turn conversation flows session memory tool calling streaming responses and human handoff.
• Build RAG pipelines: document ingestion chunking embeddings hybrid search reranking metadata filtering and source citation.
• Develop MCP servers that expose enterprise APIs and data as governed tools and integrate agents with each other using A2A.
• Drive rapid iterative delivery: ship a working MVP quickly then harden optimise and load test it for production.
• Engineer for scale: tune latency throughput and cost so the chatbot holds up under thousands of concurrent users.
• Build evaluation suites for answer quality groundedness and regression testing of prompts and models.
• Ship through CI/CD with infrastructure as code logging tracing alerting and cost monitoring.
• Work as part of the client team: estimate and break down work join weekly demos and explain technical trade-offs to stakeholders.
• Review code mentor engineers and contribute to runbooks and technical documentation for handover.

Must have

• Enterprise delivery: built and shipped at least two production-grade GenAI or conversational AI applications with ownership of significant components including one delivered on a tight timeline.
• Embedded fast-paced delivery: worked as part of consulting or client teams; comfortable with ambiguous scope weekly demos and stakeholder exposure.
• Hands-on engineering: strong production Python and REST APIs
• Conversational AI: built production chatbots or virtual assistants with multi-turn context intent handling session memory human handoff and multichannel delivery (web mobile)
• Chatbot scale: worked on chatbots running at high concurrency in production. Candidates should state peak concurrent users p95 latency and their part in scaling it.
• Scale engineering: response streaming semantic and response caching retries and rate-limit handling provisioned throughput autoscaling and load testing.
• RAG: implemented retrieval pipelines with vector stores (OpenSearch pgvector Aurora Pinecone or similar) and measured retrieval quality and groundedness.
• AWS Bedrock (essential): model invocation and selection Knowledge Bases Guardrails Agents and model evaluation.
• Bedrock AgentCore (essential): hands-on with Runtime Memory Gateway Identity and Observability to deploy and operate agents.
• MCP: built MCP servers and clients including authentication and authorisation for tools.
• A2A and multi-agent: built multi-agent workflows using A2A and frameworks such as Strands Agents LangGraph or CrewAI.
• AWS foundations: Lambda API Gateway ECS or EKS DynamoDB S3 IAM VPC networking and CloudWatch.
• Responsible AI: guardrails hallucination control prompt-injection defence and PII handling in regulated environments.
• LLM observability and evaluation: Langfuse Ragas Bedrock evaluations or similar tools to trace monitor and evaluate LLM applications.
• Location: based in or able to relocate to Atlanta; US work authorisation required.

Nice to have

• Voice AI with Amazon Connect Lex or speech models.
• Equivalent platforms on Azure OpenAI Vertex AI or Databricks Mosaic AI.
• Fine-tuning distillation or small-model deployment for cost and latency.
• Product mindset: conversational UX user feedback loops and A/B testing of prompts or flows.
• Front-end chat UI experience (React).
• AWS Certification on AI/GenAI
• Domain experience in Finance

Staffworxs is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive workplace for all employees regardless of race color religion gender sexual orientation national origin age disability or veteran status.

Required Experience:

Senior IC