We are seeking an Software engineer (Contract), specialized in AI/ML applications to independently drive the development, evaluation, deployment and end-to-end lifecycle management of our AI-powered systems. This role bridges advanced AI application development with robust software engineering and continuous automation. You will extensively leverage AI agents, design automated testing frameworks, and implement secure GitLab CI/CD pipelines to ensure code quality and system resilience. A core component of this role involves deploying and scaling models efficiently across distributed infrastructure. You will manage GPU orchestration, prompt-tune models, and design advanced AI workflows using tools like Kubernetes, Ray, or Slurm.
Key Responsibilities
* Infrastructure & Distributed Orchestration: Architect, deploy, and scale open-source models using distributed orchestration frameworks like Kubernetes, Ray, or Slurm to run highly available and fault-tolerant AI workloads.
* AI Systems & Prompt Engineering: Design experiments, prompt-tune, evaluate, and deploy production-grade models and AI agents, implementing flexible mechanisms to benchmark performance and swap models quickly to fit evolving use cases.
* Error & Gap Analysis: Run comprehensive model benchmarks, perform deep error and gap analysis on model outputs, and build analytics dashboards to communicate system performance findings effectively to stakeholders.
* Automated Testing & Coverage: Build extensive automated testing suites to validate end-to-end application code, aggressively driving improvements in test coverage across both standard software and stochastic AI outputs.
* DevSecOps Automation: Maintain clean, secure systems by automating vulnerability scanning on GitLab Merge Requests (MRs) and implementing fast remediation pipelines for identified vulnerabilities.
* Independent Execution: Take high ownership of features from ideation to production, managing architectural choices, public/private repository synchronization, and community interactions.
Technical Requirements
* Python & Systems Engineering: 4+ years of professional experience writing production-grade, asynchronous Python, with a strong focus on decoupled, clean system architecture and design patterns.
* Deployment & Orchestration: Hands-on experience with production-grade model deployment, performance monitoring and analysis; and scaling using Kubernetes, Ray, or Slurm to manage multi-node cluster configurations.
* Hardware & Scaling Optimization: Strong understanding of GPU memory management, and infrastructure-level tuning for high-throughput, low-latency AI inference workflows.
* AI Evaluation & Frameworks: Deep experience building with LangChain, Hugging Face libraries, vLLM, and SGLang. Proven expertise in prompt engineering, automated model benchmarking, and running systematic LLM evaluations.
* Data analysis: Proficient in data analysis using Python (pandas, NumPy, or similar), able to extract insights from model evaluation results and communicate findings clearly to both technical and non-technical stakeholders.
* GitLab CI/CD & Security Automation: Advanced knowledge of GitLab pipelines, specifically building automated test jobs and integrating vulnerability scanners directly into the MR workflow.
* Testing Toolchains: Expert familiarity with Python testing frameworks (e.g., PyTest), mocking libraries, and automated test generation frameworks for AI workloads.
* Advanced Version Control: High proficiency in advanced Git workflows, including rebase strategies, cryptographic commit signing, and managing complex public/private repository mirroring.
Ways to stand out
We look beyond standard resumes. You will immediately stand out if you provide:
* OSS Hyperlinks: Direct links in your resume to accepted PRs, open issues you resolved, or documentation you authored in public AI repositories like LangChain, Hugging Face, vLLM, SGLang or other public repositories.
* Agentic Case Studies: A short write-up or repository link showcasing an AI agent or multi-agent framework you built, with metrics demonstrating how you ran gap analysis or benchmarked its accuracy.
* CI/CD Showcase: A brief example or description of a GitLab/GitHub custom pipeline you designed to solve a complex testing, automation, or security scanning bottleneck.
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Key Responsibilities
* Infrastructure & Distributed Orchestration: Architect, deploy, and scale open-source models using distributed orchestration frameworks like Kubernetes, Ray, or Slurm to run highly available and fault-tolerant AI workloads.
* AI Systems & Prompt Engineering: Design experiments, prompt-tune, evaluate, and deploy production-grade models and AI agents, implementing flexible mechanisms to benchmark performance and swap models quickly to fit evolving use cases.
* Error & Gap Analysis: Run comprehensive model benchmarks, perform deep error and gap analysis on model outputs, and build analytics dashboards to communicate system performance findings effectively to stakeholders.
* Automated Testing & Coverage: Build extensive automated testing suites to validate end-to-end application code, aggressively driving improvements in test coverage across both standard software and stochastic AI outputs.
* DevSecOps Automation: Maintain clean, secure systems by automating vulnerability scanning on GitLab Merge Requests (MRs) and implementing fast remediation pipelines for identified vulnerabilities.
* Independent Execution: Take high ownership of features from ideation to production, managing architectural choices, public/private repository synchronization, and community interactions.
Technical Requirements
* Python & Systems Engineering: 4+ years of professional experience writing production-grade, asynchronous Python, with a strong focus on decoupled, clean system architecture and design patterns.
* Deployment & Orchestration: Hands-on experience with production-grade model deployment, performance monitoring and analysis; and scaling using Kubernetes, Ray, or Slurm to manage multi-node cluster configurations.
* Hardware & Scaling Optimization: Strong understanding of GPU memory management, and infrastructure-level tuning for high-throughput, low-latency AI inference workflows.
* AI Evaluation & Frameworks: Deep experience building with LangChain, Hugging Face libraries, vLLM, and SGLang. Proven expertise in prompt engineering, automated model benchmarking, and running systematic LLM evaluations.
* Data analysis: Proficient in data analysis using Python (pandas, NumPy, or similar), able to extract insights from model evaluation results and communicate findings clearly to both technical and non-technical stakeholders.
* GitLab CI/CD & Security Automation: Advanced knowledge of GitLab pipelines, specifically building automated test jobs and integrating vulnerability scanners directly into the MR workflow.
* Testing Toolchains: Expert familiarity with Python testing frameworks (e.g., PyTest), mocking libraries, and automated test generation frameworks for AI workloads.
* Advanced Version Control: High proficiency in advanced Git workflows, including rebase strategies, cryptographic commit signing, and managing complex public/private repository mirroring.
Ways to stand out
We look beyond standard resumes. You will immediately stand out if you provide:
* OSS Hyperlinks: Direct links in your resume to accepted PRs, open issues you resolved, or documentation you authored in public AI repositories like LangChain, Hugging Face, vLLM, SGLang or other public repositories.
* Agentic Case Studies: A short write-up or repository link showcasing an AI agent or multi-agent framework you built, with metrics demonstrating how you ran gap analysis or benchmarked its accuracy.
* CI/CD Showcase: A brief example or description of a GitLab/GitHub custom pipeline you designed to solve a complex testing, automation, or security scanning bottleneck.
Trinus Corporation, a leading provider of technology solutions and services with over 25 years of experience, is a certified WBE/MBE/SBE/SDB firm accredited by WBENC, NMSDC, and SBA.
Our mission is to shape the future of work by aligning the right mix of people, process, technology, and innovation to efficiently meet our clients' business objectives.
At Trinus, we understand that finding the right opportunity is pivotal in your career journey. Our staffing services go beyond mere placements; they are about matching your skills and aspirations with the perfect fit.
To learn more about us, please visit our website www.trinus.com
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