Data Tech Lead (Python+ FastAPI+ LLM+ Data Modeling+ Data Pipeline)

United Software Group, Inc.

Dallas, TX, United States

25 days ago

Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

2 years minimum

Compensation

$62,400.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Adobe InDesign Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Component-Based Software Engineering Automated Storage and Retrieval Systems Microsoft Azure Cloud Computing Cloud Database Software Quality Code Review Continuous Integration

+21 more

Information Engineering Python (Programming Language) Pair Programming Cloud Services Software Deployment SQL Databases Subsystems Systems Integration Datadog Large Language Models Snowflake Technical Debt Git Fastapi Data Layers Containerization AI Platforms Kubernetes Data Pipelines Docker Databricks

Job description

We are looking for a Tech Lead who can bridge hands-on engineering and technical leadership across Data and AI workstreams. You will guide a team of engineers, set technical direction for features and subsystems, and remain deeply involved in code quality, architecture decisions, and client-facing technical discussions. This role is for engineers who are ready to lead without stepping away from the craft. What You’ll Do

Lead the technical design and delivery of data pipelines, AI services, and agentic application components across one or more client workstreams.
Provide day-to-day technical direction to engineers: design reviews, code reviews, architectural guidance, and unblocking.
Translate ambiguous business and client requirements into clear technical designs and implementation plans.
Own code quality, testing standards, and engineering best practices within your squad.
Collaborate with AI Architects and Data Architects to ensure local technical decisions align with the broader system design.
Engage directly with client technical teams: participate in design sessions, demos, and technical walkthroughs.
Identify and address technical debt, performance bottlenecks, and reliability gaps proactively.
Mentor junior and mid-level engineers - through pair programming, structured feedback, and knowledge sharing.

What We Work On

Python-based agentic applications and AI services deployed in enterprise financial services environments.
Cloud data pipelines, semantic layers, and retrieval systems that ground AI applications in trustworthy data.
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Requirements

4 8 years of software or data engineering experience, with at least 1 2 years in a technical lead or senior individual contributor role.
Strong Python skills - FastAPI, async patterns, testing, and production deployment.
Hands-on experience with LLM agent frameworks (LangGraph, LangChain) and RAG architectures.
Solid understanding of data engineering fundamentals: SQL, data modelling, pipelines, and cloud data platforms.
Experience with Git, CI/CD, containerisation (Docker), and cloud deployments (AWS/Azure/GCP).
Clear, confident communicator - comfortable in client-facing technical discussions and written documentation., * Experience with Snowflake, Databricks, or equivalent cloud data warehouses.
Familiarity with observability tooling (OpenTelemetry, Datadog) and LLM evaluation frameworks.
Exposure to regulated environments - financial services, healthcare, or similar.
Cloud certifications (AWS/Azure/GCP) or Snowflake certification.

Benefits & conditions

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