Senior GenAI/Python Engineer

Acestack; Chicago (IL); On-site; USD 150,000 - 210,000; Full time

Job summary

Acestack in Chicago seeks a Senior GenAI/Python Engineer to build production-grade GenAI systems using Python, FastAPI, Docker, and strong software practices for reliability and scale.

You will design LLM-powered agents, including intent classification and domain workflows, translating user utterances into JSON payloads and orchestrating multi-step calls.

Qualifications

• 5+ years of advanced Python development with production-grade practices.
• Hands-on experience with GenAI/LLM production apps and model APIs.
• Experience building agents and orchestration across steps.
• Strong JSON schema enforcement and data validation.
• Experience with vector stores and semantic search concepts.
• API development with FastAPI or similar frameworks.
• Cloud experience, Azure preferred (AWS/GCP acceptable).
• Excellent written and verbal communication; collaborative.

Responsibilities

• Build and enhance LLM-powered agentic applications using Python.
• Develop intent classification and domain workflows for complex questions.
• Create pipelines converting utterances into accurate JSON payloads.
• Integrate semantic search and vector retrieval for entity resolution.
• Design, build, and consume FastAPI-based microservices.
• Implement async orchestration for parallel LLM and API calls.
• Develop prompt engineering, structured output, and guardrails.
• Create evaluation harnesses, tests, and regression suites.
• Collaborate with platform, data, service, and product teams.
• Document architectures with ADRs, diagrams, and Confluence pages.

Skills

Python development

OpenAI API

FastAPI

LLM orchestration

JSON schema validation

CI/CD

Docker

LangChain

SQL

Async Python

Cloud Azure

Education

Bachelor's degree in Computer Science or related field

Tools

Pinecone

Weaviate

OpenSearch

Snowflake

Job description

Job Title: Senior GenAI/Python Engineer

Location: Chicago, IL

Full Time

Exp:-7+Yrs

Job Description

Must Have Technical/Functional Skills

• 5+ years of advanced professional Python development experience with production-grade coding practices.
• Strong hands‑on experience writing clean, tested, maintainable code using typing, pytest, packaging standards, Git, CI/CD, Docker, and code review discipline.
• 1.5+ years of hands‑on experience building GenAI / LLM applications in production using OpenAI, Azure OpenAI, Anthropic, Bedrock, or similar model APIs.
• Experience building LLM-powered agents, including intent classification, domain‑specific agents, agentic extraction flows, and multi‑step orchestration.
• Hands‑on experience with Agentic AI frameworks or patterns such as LangChain, LangGraph, LlamaIndex, function calling, tool use, or custom orchestration.
• Strong experience in structured output extraction from LLMs using JSON schema enforcement, Pydantic, retry/repair strategies, and validation logic.
• Experience with RAG and vector search concepts including embeddings, chunking, hybrid search, reranking, entity resolution, fuzzy matching, confidence thresholds, and disambiguation flows.
• Working knowledge of vector databases or search platforms such as pgvector, Pinecone, Weaviate, OpenSearch, Snowflake vector functions, or equivalent.
• Strong API development experience using FastAPI or similar frameworks such as Flask or Django.
• Experience with async Python and orchestration of parallel LLM/API calls.
• Strong SQL skills and comfort working with large analytical datasets.
• Cloud environment experience, preferably Azure; AWS or GCP acceptable.
• Strong written and verbal communication skills, with ability to collaborate directly with engineering teams, product owners, and cross‑functional stakeholders.

Roles & Responsibilities

• Build and enhance LLM-powered agentic applications using Python.
• Develop intent classification, domain‑specialist agent workflows, and agentic extraction pipelines for complex user questions.
• Build natural‑language‑to‑structured‑payload pipelines that convert user utterances into accurate JSON query payloads, including filters, exclusions, rankings, and metric selection.
• Integrate semantic search and vector retrieval services for embedding‑based entity resolution, fuzzy matching, confidence scoring, and disambiguation flows.
• Design, build, and consume FastAPI‑based microservices.
• Implement async orchestration patterns for parallel LLM calls, API calls, and downstream service integrations.
• Develop prompt engineering patterns, structured output enforcement, JSON schema validation, function calling, tool usage, and guardrails.
• Build evaluation harnesses, test sets, and regression test frameworks to measure extraction accuracy and validate prompt/model changes.
• Work with metadata/catalog services, entitlement‑aware data access, and reporting‑engine payload contracts.
• Collaborate with multiple platform, data, service, and product teams to deliver production‑ready GenAI capabilities.
• Write clear technical documentation including Confluence pages, ADRs, sequence diagrams, and flow diagrams.
• Participate in hands on technical evaluation, code reviews, design discussions, and production readiness reviews.