TELECOMMUTE Senior AI/LLM Engineer

1. A minimum of five (5) years of experience in AI-Enhanced Software Engineering, experience shall include at least three (3) of any of the following:

a. Advanced skills in Python and strong knowledge of backend architecture.

b. Hands-on experience using AI coding assistants (such as GitHub Copilot or Cursor) to speed up software development.

c. Proven ability to set up and manage automated Continuous Integration/Continuous Deployment (CI/CD) pipelines.

d. Experience implementing AI-driven quality checks and generating unit tests within CI/CD workflows.

1. A minimum of three (3) years of experience in Advanced Large Language Model (LLM) and Agentic System Design, experience shall include at least three (3) of any of the following:

a. Hands-on experience designing multi-agent workflows that coordinate tasks across different AI agents.

b. Building and optimizing Retrieval-Augmented Generation (RAG) pipelines, including improving vector database search for faster and more accurate results.

c. Applying Chain-of-Thought reasoning techniques to support complex tasks in the Software Development Lifecycle (SDLC).

d. Using frameworks such as LangGraph, CrewAI, or AutoGPT to automate end-to-end development processes

1. A minimum of three (3) years of experience in Predictive Log and Telemetry Intelligence, experience shall include at least three (3) of any of the following:

a. Building parsers and classifiers powered by Large Language Models (LLMs).

b. Working with large, unstructured datasets such as system logs, distributed traces, and heap dumps.

c. Designing solutions that can identify patterns and predict issues before they impact system performance.

d. Applying AI techniques to improve log analysis and telemetry monitoring for faster troubleshooting.

1. A minimum of two (2) years of experience in AI Quality Guardrails, experience shall include at least three (3) of any of the following:

a. Building Human-in-the-Loop systems where humans review and validate AI outputs for accuracy and safety.

b. Creating automated evaluation frameworks such as Retrieval Augmented Generation Assessment (RAGAS) and Generative Evaluation (G-Eval) to measure AI performance.

c. Implementing safeguards to prevent hallucinations (incorrect or fabricated outputs) in technical results.

d. Designing strategies to mitigate prompt-injection risks for autonomous AI agents, ensuring secure and reliable operations.

Infinite Solutions Inc. is a California-based Information Technology Solution provider specializing in delivering enterprise technology and digital transformation solutions for public-sector clients since 1997. With deep expertise in systems integration, ERP implementations, data analytics, and modernization, we support mission-critical initiatives for State and local agencies. Our team is known for combining technical excellence with a practical, results-driven approach to solving complex business challenges. At Infinite Solutions, we are committed to innovation, collaboration, and delivering measurable outcomes that make a meaningful impact.

To continue delivering cutting-edge services and solutions to our clients, we are actively seeking qualified and dynamic professionals to strengthen and grow our practice.