Sr.AI Engineer

TATA Consulting Services•Des Moines, IA

32d•$85,000 - $105,000

About The Position

Sr. AI Engineer Must Have Technical/Functional Skills Build, deploy, and optimize production-grade AI applications leveraging GenAI, Agentic AI, and ML. Lead design and scaling of RAG pipelines, vector search systems, and LLM evaluation workflows. Develop AI agents with LangChain, AutoGen, LlamaIndex, or LangGraph for task automation and decision support. Translate complex business problems into end-to-end AI solutions using AWS-native services. Ingest and process unstructured/structured data (parsing, chunking, embeddings, retrieval). Deliver intuitive user experiences integrating LLMs and intelligent agents into real-time workflows. Integrate and evaluate enterprise AI tools such as Claude, GPT-4/4o, ChatGPT Enterprise, Copilot, Glean, Shelf, and Genesys AI. Drive innovation in document automation (summarization, translation, NER) and multilingual NLP. Implement observability, governance, and responsible AI practices for secure, compliant deployments. Collaborate across IT, data, legal, compliance, and business teams on high-impact solutions. Mentor engineers and lead specific workstreams to advance Athene's AI platform. Roles & Responsibilities 6+ years in software engineering or data science, with 2+ years in GenAI/LLM/Agentic AI. Proficiency in Python, REST APIs, React/Node.js, and tools like OpenAPI, JSON, and YAML. Hands-on experience with AWS AI services (Bedrock, SageMaker, Nova, Textract, Translate, Lambda, Step Functions). Strong understanding of LLMs, embeddings, prompt engineering, and tool use. Comfortable with CI/CD pipelines, Docker, and cloud-native infrastructure. Solid foundation in software engineering, backend performance, observability, and security. Experience with enterprise-grade AI tools like Claude, GPT-4/4o, and ChatGPT Enterprise. Insurance or financial services experience, plus knowledge of regulatory and compliance requirements (preferred). Product-oriented mindset: rapidly prototype, iterate, test and deliver business-facing AI features. Track record of mentorship and technical leadership in AI-focused teams.

Requirements

6+ years in software engineering or data science, with 2+ years in GenAI/LLM/Agentic AI.
Proficiency in Python, REST APIs, React/Node.js, and tools like OpenAPI, JSON, and YAML.
Hands-on experience with AWS AI services (Bedrock, SageMaker, Nova, Textract, Translate, Lambda, Step Functions).
Strong understanding of LLMs, embeddings, prompt engineering, and tool use.
Comfortable with CI/CD pipelines, Docker, and cloud-native infrastructure.
Solid foundation in software engineering, backend performance, observability, and security.
Experience with enterprise-grade AI tools like Claude, GPT-4/4o, and ChatGPT Enterprise.
Product-oriented mindset: rapidly prototype, iterate, test and deliver business-facing AI features.
Track record of mentorship and technical leadership in AI-focused teams.

Nice To Haves

Insurance or financial services experience, plus knowledge of regulatory and compliance requirements (preferred).

Responsibilities

Build, deploy, and optimize production-grade AI applications leveraging GenAI, Agentic AI, and ML.
Lead design and scaling of RAG pipelines, vector search systems, and LLM evaluation workflows.
Develop AI agents with LangChain, AutoGen, LlamaIndex, or LangGraph for task automation and decision support.
Translate complex business problems into end-to-end AI solutions using AWS-native services.
Ingest and process unstructured/structured data (parsing, chunking, embeddings, retrieval).
Deliver intuitive user experiences integrating LLMs and intelligent agents into real-time workflows.
Integrate and evaluate enterprise AI tools such as Claude, GPT-4/4o, ChatGPT Enterprise, Copilot, Glean, Shelf, and Genesys AI.
Drive innovation in document automation (summarization, translation, NER) and multilingual NLP.
Implement observability, governance, and responsible AI practices for secure, compliant deployments.
Collaborate across IT, data, legal, compliance, and business teams on high-impact solutions.
Mentor engineers and lead specific workstreams to advance Athene's AI platform.