1-YEAR BASE TERM, WITH POTENTIAL EXTENSION IF CONTRACT HOURS STILL REMAIN AFTER BASE TERM. CAN BE PERFORMED REMOTELY OR ONSITE IN SACRAMENTO, CA AREA.
Mandatory Requirements
- 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:
- Advanced skills in Python and strong knowledge of backend architecture.
- Hands-on experience using AI coding assistants (such as GitHub Copilot or Cursor) to speed up software development.
- Proven ability to set up and manage automated Continuous Integration/Continuous Deployment (CI/CD) pipelines.
- Experience implementing AI-driven quality checks and generating unit tests within CI/CD workflows.
- 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:
- Hands-on experience designing multi-agent workflows that coordinate tasks across different AI agents.
- Building and optimizing Retrieval Augmented Generation (RAG) pipelines, including improving vector database search for faster and more accurate results.
- Applying Chain of Thought reasoning techniques to support complex tasks in the Software Development Lifecycle (SDLC).
- Using frameworks such as LangGraph, CrewAI, or AutoGPT to automate end-to-end development processes.
- 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:
- Building parsers and classifiers powered by Large Language Models (LLMs).
- Working with large, unstructured datasets such as system logs, distributed tracers, and heap dumps.
- Designing solutions that can identify patterns and predict issues before they impact system performance.
- Applying AI techniques to improve log analysis and telemetry monitoring for faster troubleshooting.
- A minimum of two (2) years of experience in AI Quality Guardrails. Experience shall include at least three of any of the following:
- Building Human-in-the-Loop systems where humans review and validate AI outputs for accuracy and safety.
- Creating automated evaluation frameworks such as Retrieval Augmented Generation Assessment (RAGAS) and Generative Evaluation (G-Eval) to measure AI performance.
- Implementing safeguards to prevent hallucinations (incorrect or fabricated outputs) in technical results.
- Designing strategies to mitigate prompt injection risks for autonomous AI agents, ensuring secure and reliable operations.
Applications that do not complete the Prescreen Survey will not be considered.
Anvaya Solutions, Inc. is an equal opportunity employer. All employment decisions, including hiring, promotions, and compensation, are made without regard to race, color, religion, sex, national origin, or any other protected characteristic. We are committed to a merit-based workplace where every individual is treated with respect and has equal access to opportunities based solely on their qualifications and performance.