PythonAbout Logikality
Logikality is building an AI-native mortgage intelligence platform for the U.S. mortgage industry. We are reimagining how mortgage operations are executed by combining AI, workflow automation, and domain expertise to solve one of the most document-intensive and decision-heavy industries in the world.
Our platform goes beyond document extraction. We are building AI systems that understand mortgage files, reason across multiple sources of information, identify risks and exceptions, support underwriting and quality control decisions, and continuously improve through expert feedback and rigorous evaluation.
Job Description
We are looking for a Generative AI Engineer to build and scale Logikality's AI-native mortgage platform.
The role requires strong hands-on engineering expertise in designing, building, and deploying production-grade Generative AI systems that power intelligent mortgage operations. You will work across LLM applications, AI agents, retrieval systems, reasoning workflows, backend services, APIs, and cloud infrastructure to transform complex mortgage workflows into reliable AI products.
This is a high-ownership role for someone who can rapidly convert business problems into scalable AI solutions with minimal supervision.
Key Requirements
- 3 to 8 years of experience in software engineering, AI engineering, or Generative AI development, preferably in startup environments.
- B.E./B.Tech. in Computer Science or a related engineering discipline a premier engineering institution (e.g., IITs, IISc, NITs, BITS Pilani, or top-tier global universities).
- Proven experience independently owning projects end-to-end from solution design and model integration to production deployment, monitoring, and maintenance.
- Strong proficiency in Python and modern backend development.
- Hands-on experience building production-grade applications using Large Language Models (LLMs).
- Experience with agentic AI frameworks, multi-agent workflows, function/tool calling, structured outputs, and prompt engineering.
- Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, vector databases, semantic search, and knowledge retrieval systems.
- Experience integrating commercial and open-source foundation models (OpenAI, Anthropic, Gemini, Llama, Mistral, or similar).
- Experience building AI pipelines using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or equivalent orchestration frameworks.
- Strong understanding of model evaluation, hallucination mitigation, guardrails, prompt optimisation, and LLM observability.
- Experience with OCR, document intelligence, structured information extraction, or multimodal AI systems is preferred.
- Strong knowledge of APIs, databases, cloud infrastructure, Docker, Kubernetes, and CI/CD pipelines.
- Ability to design scalable, secure, and production-ready AI architectures.
- Strong debugging skills, systems thinking, and an ownership mindset with the ability to move quickly in an early-stage startup.
Preferred Experience
- Experience building AI copilots, autonomous agents, or enterprise AI assistants.
- Familiarity with MCP, AI tool integration, and agent orchestration.
- Experience fine-tuning, distillation, or evaluation of open-source LLMs.
- Knowledge of AI safety, governance, and responsible AI practices.
- Experience working with document-heavy enterprise domains such as financial services, banking, insurance, healthcare, legal, or mortgage technology.
- Experience deploying AI applications on AWS, Azure, or GCP.
What You'll Build
- AI agents that automate mortgage underwriting, quality control, compliance, and document review.
- RAG-based knowledge systems that reason across large collections of mortgage documents.
- Intelligent workflows combining LLM reasoning with deterministic business rules.
- Production-grade AI APIs and backend services powering Logikality's platform.
- Evaluation pipelines to continuously improve AI quality, accuracy, latency, and cost.
Why Join Logikality?
At Logikality, you'll work on problems that require genuine reasoning, not just text generation. You'll help build AI systems that understand complex documents, synthesise information across workflows, explain decisions, identify exceptions, and improve through continuous learning and expert feedback.
This will be a full-time in-office role based in Bangalore. Immediate joiners are preferred.
Shubham Vishwakarma
Full Stack Developer - Averlon
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