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# Lead Engineer - App Engg & AI

- **Company:** Maruthi Technologies Inc
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software Design Documents, Identity and Access Management, Python (Programming Language), Open Source Technology, OpenAI, Next.js, Search Technologies, Software Engineering, Amazon Connect, Simple Object Database Access, ReactJS, Retrieval-Augmented Generation, Large Language Models, Snowflake, Spring-boot, AI Platforms, Collibra, Serverless Computing, Agent2Agent Protocol
- **Published:** October 17, 2026
- **Apply:** https://www.careerbuilder.com/job-details/lead-engineer-app-engg-ai-dallas-tx--feead66b-d355-4eef-884f-c7da048c0ea0

## About the Role

* 7+ years in software engineering with 2+ years shipping LLM or agentic systems to production.
 * Hands-on depth in Python or Java/Spring Boot, plus comfort in a modern front-end stack (React/Next.js) when the engagement needs it.
 * Working knowledge of a major cloud (AWS or Azure) including managed AI services, containers, serverless, and IAM.
 * Experience with RAG, vector search, and evaluation methodology - including a clear-eyed view of where retrieval is the wrong answer.
 * Demonstrated technical leadership of a small team on a delivery-pressured project.
 * Strong written and verbal communication; you can write a design doc a client will actually read.

Preferred

 * Consulting delivery experience in a regulated vertical (financial services, healthcare, retail data, nonprofit/crisis services).
 * MCP, A2A, or comparable agent interoperability protocol work.
 * Snowflake, Collibra, SODA, or data quality tooling exposure.
 * Experience with contact center or omnichannel platforms (Amazon Connect, Teams, voice).

## Description

ResponsibilitiesTranslate business outcomes into agent specifications, tool definitions, evaluation criteria, and acceptance gates.Implement production agentic workflows: retrieval, tool orchestration, structured output, human approval loops, failure handling and fallback.Own evaluation for your engagement: define what "good" means, build the harnessRun agile ceremonies for the pod; produce estimates and sprint plansApp Development: Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama).Required Qualifications7+ years in software engineering with 2+ years shipping LLM or agentic systems to production.Hands-on depth in Python or Java/Spring Boot, plus comfort in a modern front-end stack (React/Next.js) when the engagement needs it.Working knowledge of a major cloud (AWS or Azure) including managed AI services, containers, serverless, and IAM.Experience with RAG, vector search, and evaluation methodology - including a clear-eyed view of where retrieval is the wrong answer.Demonstrated technical leadership of a small team on a delivery-pressured project.Strong written and verbal communication; you can write a design doc a client will actually read.PreferredConsulting delivery experience in a regulated vertical (financial services, healthcare, retail data, nonprofit/crisis services).MCP, A2A, or comparable agent interoperability protocol work.Snowflake, Collibra, SODA, or data quality tooling exposure.Experience with contact center or omnichannel platforms (Amazon Connect, Teams, voice).