Infrastructure & AI Integration Engineer

C2C is not available

Job Description

Key Qualifications:

• Minimum 5 years of experience as a Python developer for DevOps infrastructure
• Ideating, architecting, and writing code more efficiently with the use of AI tools
• Strong python with Node.js
• Some testing frameworks, like Selenium would be helpful
• CI/CD & Infrastructure Hands-on experience building and maintaining CI/CD pipelines using Kubernetes-native build and delivery systems (e.g., Rio or similar)
• Strong proficiency with Kubernetes — including writing manifests, Helm charts, and managing deployments
• Experience with container build systems and orchestration (Docker, image registries, rolling deployments)
• Ability to debug pipeline failures, optimize build performance, and manage multi-environment deployments (dev/staging/prod)
• Full Stack Development Proficient in Python for backend services, scripting, and data processing
• Proficient in Node.js for API development and server-side applications
• Experience with relational and document databases (PostgreSQL, MongoDB) — schema design, query optimization, and migrations
• Experience designing and consuming RESTful APIs and/or GraphQL
• Comfortable working across frontend and backend layers of a service
• Ai Feature Implementation Working knowledge of LLM APIs (e.g., Claude, Gemini, or similar) and how to integrate them into production applications
• Experience building agentic workflows — multi-step, tool-using AI agents that reason and act autonomously
• Ability to design deterministic AI flows — structured, rule-guided pipelines that ensure predictable AI outputs (e.g., RAG pipelines, prompt chaining, output validation)
• Understanding of when to apply agentic vs. deterministic approaches based on use case requirements
• Prompt engineering — designing, iterating, and versioning prompts for reliability and consistency
• Evaluation & observability — measuring AI output quality through automated evals, regression detection, and human-in-the-loop review
• Context management — working within token limits, chunking strategies, and structuring input for optimal results
• Cost & latency optimization — caching, model tier selection, batching, and streaming strategies for production workloads
• Safety & guardrails — output validation, handling hallucinations, content filtering, and knowing when AI is not the right solution

Soft Skills & Work Style

• Team Integration: Comfortable integrating into an existing infra team quickly, collaborative, low-friction, and communicates proactively
• Deadline-Driven: Consistently delivers work on time, raises blockers early and manages scope without missing commitments
• Problem Solver: Strong analytical and debugging skills, approaches complex issues methodically and independently
• Quick Learner: Able to ramp up on unfamiliar internal services, platforms, and tooling rapidly when provided documentation
• Security Mindset: Treats security as a first-class concern throughout development and infrastructure work

Nice to Have

• Experience with Playwright or similar end-to-end testing frameworks
• Familiarity with WebSocket/real-time communication (Socket.IO)
• Familiarity with monitoring and logging tools (Grafana, Splunk, or similar)