AI/ML Engineer

Role overview

AI/ML Engineer at AppZen

LLM & Agent Development: Build and improve LLM-powered features and multi-step agentic workflows (e.g., using Lang Graph) that extract, validate and reason over invoices, receipts, expense reports and card transactions.

We are looking for an AI/ML Engineer with 1–3 years of experience to join our growing AI team.

Responsibilities

• You will work alongside senior AI/ML engineers, data scientists and product managers to take features from prototype to production, and own them once they are live.
• Retrieval-Augmented Generation (RAG): Build retrieval pipelines (chunking, embeddings, vector search and re-ranking) that give models the right policy, vendor and transaction context to make accurate financial decisions.
• Tool Use & Structured Outputs: Implement function calling and API integrations so that models can reliably query internal services and ERP/AP systems, and return validated, structured (JSON) outputs.
• Evaluation & Quality: Build evaluation datasets, metrics and automated test suites to measure accuracy, hallucination rate, latency and cost, and use the results to improve prompts, retrieval and models.
• Production Engineering: Package and deploy models and services using Docker and CI/CD pipelines, add monitoring and logging, and keep them reliable, scalable and cost-efficient in production.
• Cross-functional Collaboration: Work closely with senior engineers, data scientists and product managers to turn customer and business requirements into well-scoped technical solutions, and contribute to code reviews and design discussions.

Required qualifications

• 1–3 years of experience building and deploying ML/AI solutions in production, including at least 1 year of hands-on work on LLM-based applications.
• Programming: Strong Python skills, with experience writing clean, tested, production-grade code and building REST APIs (e.g., Fast API or Flask).
• LLM & Agent Frameworks: Hands-on experience with Lang Chain, Lang Graph, Llama Index or similar frameworks, and with LLM APIs (e.g., Open AI, Anthropic, Gemini) or open-source models.
• RAG & Vector Databases: Practical experience building RAG pipelines using vector databases such as Pinecone, Milvus, pgvector or FAISS .
• Prompting & Structured Outputs: Good understanding of prompting techniques (few-shot, Chain-of-Thought, Re Act) and of getting reliable structured outputs and function calls from LLMs.
• ML Fundamentals: Solid grounding in ML and NLP fundamentals, with working experience in Py Torch or a similar framework.
• Exposure to fine-tuning (e.g., Lo RA) is a plus.
• MLOps & Cloud: Working knowledge of Docker, Git and CI/CD, and experience deploying on a cloud platform (AWS, GCP or Azure).
• Familiarity with LLM observability tools (e.g., Lang Smith, Arize Phoenix or Weights & Biases) is a plus.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• We may use artificial intelligence tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
• These tools assist our recruitment team but do not replace human judgment.
• Final hiring decisions are ultimately made by humans. apply for this job App Zen, Inc.
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Required skills

• Professional

Preferred qualifications and skills

• Experience with document AI (OCR, invoice or receipt data extraction) or with finance, accounts payable or expense data.

Employment details

• Location: Pune

About the employer

• To learn more, visit us at www.appzen.com.

Additional role details

• App Zen is the leader in autonomous spend-to-pay software.
• Its patented artificial intelligence accurately and efficiently processes information from thousands of data sources so that organizations can better understand enterprise spend at scale to make smarter business decisions.
• It seamlessly integrates with existing accounts payable, expense, and card workflows to read, understand, and make real-time decisions based on your unique spend profile, leading to faster processing times and fewer instances of fraud or wasteful spend.
• Global enterprises, including one-third of the Fortune 500, use App Zen’s invoice, expense, and card transaction solutions to replace manual finance processes and accelerate the speed and agility of their businesses.
• About the
• ROLE:
• In this role, you will build and ship the LLM-powered and agentic features that read, understand and make decisions on invoices, expense reports and card transactions for some of the world’s largest finance teams.
• If you enjoy turning the latest advances in LLMs and agents into reliable and measurable products, App Zen is the place for you.