AI Engineer (LLM Agents & Workflow Automation)
Quick Summary
Build and deploy LLM-based agents and intelligent workflows that automate operational tasks, process information, and improve business efficiency.
As an AI Engineer, you will design, develop, and deploy intelligent workflows and AI-powered agents that solve real-world operational challenges in the mortgage industry. You will work closely with engineers, domain experts, and US-based clients to understand business processes and turn them into practical AI solutions. From automating document collection and verification to streamlining borrower communication and loan processing, your work will have a direct impact on business efficiency. You will take ownership of projects from initial problem discovery through production deployment and continuous improvement. Working in a collaborative, client-focused environment, you will have the opportunity to experiment with modern LLM technologies and build solutions used by real customers. This is an excellent opportunity for an early-career engineer looking to grow in applied AI and workflow automation.
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Understand client workflows: Collaborate directly with client stakeholders, operational teams, and domain experts to understand existing processes, systems, business challenges, and automation opportunities.
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Identify and scope AI solutions: Translate business problems into clearly defined technical requirements, establishing measurable success criteria and practical implementation plans.
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Develop AI-powered agents: Build and deploy LLM-based agents and intelligent workflows that automate operational tasks, process information, and improve business efficiency.
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Build system integrations: Connect AI solutions with client applications, APIs, databases, and third-party platforms to enable seamless information exchange and workflow automation.
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Ensure production readiness: Implement essential production capabilities, including conversation history, logging, monitoring, exception handling, human review, and escalation mechanisms.
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Manage deployment and optimization: Release solutions to real users, monitor performance, resolve unexpected issues, and deliver regular improvements based on operational feedback.
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Measure business impact: Track and evaluate solution performance through metrics such as processing time, accuracy, manual effort reduction, and overall team productivity.
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Take end-to-end ownership: Manage assigned projects from problem identification and development through deployment, maintenance, and continuous enhancement.
Requirements
~2 min read-
Professional experience: 1.5–4 years of software engineering experience, including hands-on experience developing applications powered by Large Language Models (LLMs).
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Programming skills: Strong proficiency in Python and the ability to build reliable, maintainable applications.
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LLM expertise: Practical experience working with LLM APIs such as OpenAI, Anthropic, or equivalent platforms.
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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.
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Integration capabilities: Experience connecting applications with APIs, databases, and third-party systems to build functional, interconnected solutions.
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Production engineering: Understanding of how to deploy and maintain AI applications, including monitoring, logging, exception handling, and output reliability.
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Communication skills: Excellent written and spoken English, with the confidence to communicate directly with US-based clients and technical stakeholders.
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Ownership mindset: Ability to independently take responsibility for a defined problem, make technical decisions, and deliver a working solution from initial discovery to production.
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Problem-solving abilities: Strong analytical thinking, adaptability, and enthusiasm for learning new technologies and understanding unfamiliar business processes.
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Experience in fintech, lending, mortgage, or other document-intensive industries.
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Familiarity with OCR technologies, intelligent document processing, or document AI solutions.
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Experience evaluating LLM outputs for accuracy, consistency, and reliability.
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Exposure to production monitoring and performance optimization for AI-powered applications.
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A bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.
Nice to have:
What We Offer
~2 min readLocation & Eligibility
About this job
- Who can apply
- India
- Posted
- 3 days ago
Listing Details
- Posted
- November 4, 2026
- First seen
- November 4, 2026
- Last seen
- November 7, 2026
Posting Health
- Days active
- 3
- Repost count
- 1
- Trust Level
- 62%
- Scored at
- November 8, 2026
Signal breakdown
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