AI Engineer

Job Overview At Entropy AI, we're building intelligence and agentic workflow infrastructure for financial services. Our systems help enterprises automate and improve real-world journeys across acquisition, qualification, onboarding, renewals, customer service, collections, and assisted decisioning. As an AI Engineer at Entropy AI, you will design, build, deploy, and continuously improve production-grade AI agents embedded inside enterprise workflows. This is not a prompt-only role. You will own both the AI behaviour and the software systems around it: orchestration, APIs, state, latency, reliability, evaluation, observability, security, and measurable business outcomes. You'll work closely with product, engineering, and business teams to convert complex BFSI workflows into dependable AI systems that can listen, reason, call tools, complete tasks, escalate safely, and operate reliably in production. Key Responsibilities Build real-time voice agents with robust turn-taking, interruption handling, streaming, tool execution, escalation, and multilingual support. Design embedded AI agents for acquisition, onboarding, qualification, servicing, renewals, retention, and operations workflows. Develop orchestration and state-management layers that reliably execute multi-step workflows across internal and third-party systems. Integrate LLMs, speech-to-text, text-to-speech, telephony systems, APIs, databases, CRMs, queues, vector stores, and internal services. Build evaluation frameworks covering task completion, tool accuracy, hallucination, policy adherence, latency, containment, transfer quality, and cost. Implement observability using structured logs, traces, conversation analytics, alerting, and failure-replay mechanisms. Optimise model selection, prompts, caching, retrieval, concurrency, and fallbacks for quality, speed, reliability, and unit economics. Partner with product, business, and customer teams to convert ambiguous workflows into production specifications and measurable acceptance criteria. Own engineering quality through clean code, automated tests, code reviews, deployment pipelines, runbooks, and incident learning. Document architecture, failure modes, evaluation methodology, and deployment processes so systems can scale beyond the original builder.

Pay: ₹700,000.00 - ₹900,000.00 per year

Benefits:

• Internet reimbursement
• Leave encashment
• Paid time off
• Provident Fund

Work Location: In person