AI Engineer (LLM Agents & Workflow Automation)

Accountabilities:: Understand client workflows: Collaborate directly with client stakeholders, operational teams, and domain experts to understand existing processes, systems, business challenges, and automation opportunities. Identify and scope AI solutions: Translate business problems into clearly defined technical requirements, establishing measurable success criteria and practical implementation plans. Develop AI-powered agents: Build and deploy LLM-based agents and intelligent workflows that automate operational tasks, process information, and improve business efficiency. Build system integrations: Connect AI solutions with client applications, APIs, databases, and third-party platforms to enable seamless information exchange and workflow automation. Ensure production readiness: Implement essential production capabilities, including conversation history, logging, monitoring, exception handling, human review, and escalation mechanisms. Manage deployment and optimization: Release solutions to real users, monitor performance, resolve unexpected issues, and deliver regular improvements based on operational feedback. Measure business impact: Track and evaluate solution performance through metrics such as processing time, accuracy, manual effort reduction, and overall team productivity. Take end-to-end ownership: Manage assigned projects from problem identification and development through deployment, maintenance, and continuous enhancement. Requirements: Professional experience: 1.5–4 years of software engineering experience, including hands-on experience developing applications powered by Large Language Models (LLMs). Programming skills: Strong proficiency in Python and the ability to build reliable, maintainable applications. LLM expertise: Practical experience working with LLM APIs such as OpenAI, Anthropic, or equivalent platforms. Agent and RAG frameworks: Familiarity with frameworks such as LangChain or LangGraph and experience developing AI agents, retrieval-augmented generation (RAG) systems, or LLM-powered workflows. Integration capabilities: Experience connecting applications with APIs, databases, and third-party systems to build functional, interconnected solutions. Production engineering: Understanding of how to deploy and maintain AI applications, including monitoring, logging, exception handling, and output reliability. Communication skills: Excellent written and spoken English, with the confidence to communicate directly with US-based clients and technical stakeholders. Ownership mindset: Ability to independently take responsibility for a defined problem, make technical decisions, and deliver a working solution from initial discovery to production. Problem-solving abilities: Strong analytical thinking, adaptability, and enthusiasm for learning new technologies and understanding unfamiliar business processes. Nice to have: Experience in fintech, lending, mortgage, or other document-intensive industries. Familiarity with OCR technologies, intelligent document processing, or document AI solutions. Experience evaluating LLM outputs for accuracy, consistency, and reliability. Exposure to production monitoring and performance optimization for AI-powered applications. A bachelor's degree in Computer Science, Software Engineering, or a related technical discipline. Benefits: Competitive compensation: Annual salary ranging from INR 14,50,000 to INR 25,00,000. Stock ownership: Opportunity to receive equity alongside your salary. Fully remote: Work remotely from anywhere in India. Direct collaboration: Work closely with the founder, engineering team, and industry experts. Meaningful ownership: Take responsibility for AI projects and influence measurable client outcomes from an early stage. Real-world AI exposure: Build and deploy intelligent agents used by mortgage professionals in the US. Career development: Gain hands-on experience with modern LLM technologies, AI agents, and production-grade workflow automation.