AI Training Data Engineer (DevOps & Backend Specialist)

Type: Freelance / Contract | Remote (India)

Experience: 3–8 years

90 Positions

About the Work

You will be contributing to the development of next-generation AI systems by creating and curating high-quality training data for reinforcement learning of agentic AI models. This includes writing realistic engineering tasks, generating and evaluating code solutions, and providing expert judgment on AI-generated outputs. Your work directly shapes how AI agents learn and improve.

What You'll Do

- Design and document realistic DevOps and backend engineering scenarios that serve as benchmark tasks for AI training
- Write, review, and rank code solutions (Python, Bash, infrastructure-as-code) that an AI agent would be evaluated against
- Evaluate AI-generated code and agentic task completions for correctness, security,

efficiency, and style

- Create detailed acceptance criteria and ground-truth solutions for complex engineering workflows
- Contribute to CI/CD, observability, Kubernetes, and infrastructure-as-code task libraries
- Collaborate with the team to ensure task diversity, difficulty calibration, and real-world relevance

Required Skills & Experience:

- 3–8 years of hands-on software engineering experience (product companies strongly preferred)
- CS degree at undergraduate level (must have)




- Solid proficiency in Python and at least one of: Bash, Go, or similar
- Solid experience with Kubernetes, Docker, and container orchestration
- Hands-on experience with CI/CD pipelines (GitLab CI or GitHub Actions preferred)
- Working knowledge of Terraform or other infrastructure-as-code tools
- Familiarity with at least 3 of the following: Prometheus + Grafana, Keycloak/IAM, gRPC,

k3s/k9s, PostgreSQL, Redis, API design

Strongly Preferred

- Experience writing technical documentation, runbooks, or engineering specs
- Ability to clearly articulate why a solution is correct, efficient, or secure
- Exposure to LLM-based coding tools (e.g., GitHub Copilot, Cursor, Claude Code) —

understanding their strengths and failure modes is a plus

- Prior experience in AI data annotation, RLHF, or technical content creation is a significant advantage

Work Dynamics

- Fully remote, freelance engagement from anywhere in India
- Output-based compensation tied to the quality, completeness, and technical complexity of deliverables
- Clear acceptance criteria provided upfront for every task
- Flexible pacing — high-performing contributors typically complete multiple tasks per week
- Must have a high-performance laptop/desktop and reliable high-speed internet

📌 AI Training Data Engineer (DevOps & Backend Specialist) (Uttar Pradesh)
🏢 Sparix Global
📍 Uttar Pradesh