The Role
Lead development of production agentic AI applications, translating business outcomes into agent specifications, tools, evaluations, and acceptance criteria. Build retrieval, orchestration, structured-output, approval, fallback, and failure-handling workflows using LLMs and APIs. Own evaluation harnesses, lead agile ceremonies, estimate work, and create sprint plans. Develop applications with Python or Java/Spring Boot and modern front-end technologies, while providing technical leadership and client-ready communication.
Summary Generated by Built In
Responsibilities
Required Qualifications
- Translate 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 harness
- Run agile ceremonies for the pod; produce estimates and sprint plans
- App Development: Build functional applications using large language models (LLMs) and APIs (e.g., OpenAI, Anthropic, open-source Llama).
- 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.
- 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).
Skills Required
- 7+ years of software engineering experience
- 2+ years shipping LLM or agentic systems to production
- Hands-on experience with Python or Java/Spring Boot
- Comfort with a modern front-end stack such as React or Next.js
- Working knowledge of AWS or Azure, including managed AI services, containers, serverless, and IAM
- Experience with RAG, vector search, and evaluation methodology
- Technical leadership of a small team on a delivery-pressured project
- Strong written and verbal communication skills
- Consulting delivery experience in a regulated vertical
- Experience with MCP, A2A, or comparable agent interoperability protocols
- Exposure to Snowflake, Collibra, SODA, or data quality tooling
- Experience with contact center or omnichannel platforms such as Amazon Connect, Teams, or voice platforms
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The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
