About Cenara Cenara helps revenue teams make better decisions about where to focus and what to do next. It connects context from customer conversations and business systems so teams can recognise risks and opportunities, understand what matters, and act with confidence. What you’ll do You'll own production AI agents and the backend services behind them, from customer problem to reliable operation. Work directly with the founder, engineers, and customers to turn business needs into systems that hold up in daily use. You'll use AI coding tools heavily, with responsibility for every line you ship.
• Design and ship systems. Build maintainable services, APIs, data models, and integrations. Own architecture, testing, deployment, and operation, including permissions, concurrency, retries, and recovery.
• Build reliable agents. Own retrieval, context, memory, tool use, and orchestration, with transparent boundaries for human review and approval.
• Diagnose failures. Trace unexpected outputs and incomplete actions to their cause across models, prompts, context, tools, and code. Ship fixes and turn failures into regression cases.
• Evaluate every update. Build automated evaluations around realistic scenarios, task completion, correctness, and behavior. Run them whenever models, prompts, tools, workflows, or scenarios change, and use the results to gate releases.
• Monitor traces, outcomes, user feedback, latency, and cost. Spot regressions and turn production findings into better behavior and reliability.
• Put research to work. Assess emerging AI research, models, and tooling through focused prototypes and benchmarks.



Adopt changes when they measurably improve quality, reliability, latency, or cost.
• Help customers deploy. Turn real workflows into pilots and production integrations. Lead technical walkthroughs and code reviews, and capture reusable patterns in documentation and examples. This role is ideal if you
• Are product-minded, low-ego, and accountable for outcomes, not just assigned code.
• Explain technical decisions clearly and collaborate well with customers and engineers.
• Make pragmatic trade-offs, including knowing when a simpler workflow is enough.
• Are comfortable unblocking yourself without detailed specifications. Minimum
• 3–7 years of hands-on software engineering experience building and operating production systems.
• Strong programming skills in Python or TypeScript, with sound software design, testing, and debugging fundamentals.
• Strong backend engineering fundamentals across APIs, databases, asynchronous execution, and cloud infrastructure.
• Production experience with LLM agents across prompting, retrieval, context management, memory, orchestration, and tool integrations such as MCP.
• Experience building automated evaluation suites and using execution traces to diagnose and fix agent failures.
• A track record of independently delivering significant features or services end to end. Backgrounds that tend to succeed
• Backend or product engineers who've owned services and AI features in production.
• Forward-deployed engineers who've turned customer problems into reliable software.
• Former technical founders or early engineers who've built and operated a product from scratch.

📌 Full-Stack AI Engineer (India)
🏢 Cenara AI
📍 India