--- title: 'AI/ML Engineer at AppZen, Inc.' canonical: 'https://feeny.ai/job/ai-ml-engineer-appzen-inc-pune-b347dtv8ezhz' type: 'job' last_seen: '2026-10-21' --- # AI/ML Engineer at AppZen, Inc. - **Company:** AppZen, Inc. - **Location:** Pune, India - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-10-15 - **Last confirmed live:** 2026-10-21 - **Apply:** https://jobs.lever.co/appzen/cce93662-196a-4814-b80c-bfa0b37384af ## Job description AppZen 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 AppZen’s invoice, expense, and card transaction solutions to replace manual finance processes and accelerate the speed and agility of their businesses. To learn more, visit us at www.appzen.com. About the role : We are looking for an AI/ML Engineer with 1–3 years of experience to join our growing AI team. 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. 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. If you enjoy turning the latest advances in LLMs and agents into reliable and measurable products, AppZen is the place for you. Key Responsibilities : - LLM & Agent Development: Build and improve LLM-powered features and multi-step agentic workflows (e.g., using LangGraph) that extract, validate and reason over invoices, receipts, expense reports and card transactions. - 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 Skills : - Professional Experience: 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., FastAPI or Flask). - LLM & Agent Frameworks: Hands-on experience with LangChain, LangGraph, LlamaIndex or similar frameworks, and with LLM APIs (e.g., OpenAI, 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, ReAct) and of getting reliable structured outputs and function calls from LLMs. - ML Fundamentals: Solid grounding in ML and NLP fundamentals, with working experience in PyTorch or a similar framework. Exposure to fine-tuning (e.g., LoRA) 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., LangSmith, Arize Phoenix or Weights & Biases) is a plus. - Good to Have: Experience with document AI (OCR, invoice or receipt data extraction) or with finance, accounts payable or expense data. - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. ## About AppZen, Inc. ## Company Overview - **One-liner**: AppZen provides AI-powered finance automation for accounts payable, expense auditing, and corporate card compliance, helping enterprises automate and control spend. - **Entity Type**: Private (Series D) - **Headquarters**: San Jose, California, United States - **Founded**: 2012 - **Founders**: Anant Kale (Co-Founder & CEO), Kunal Verma (Co-Founder & CTO) ## Core Business - **Primary industries**: Software Development; AI-powered Finance Automation; Spend Management - **Target customers**: B2B, Enterprise – global companies, including one-third of the Fortune 500, across higher education, life sciences, manufacturing, and more - **Mission**: "Empower teams with tools that simplify workflows, reduce costs, and drive smarter decisions" using AI for finance operations ## Products & Services - **Mastermind AI Automation Platform**: The core AI platform that automates finance workflows, integrating with existing AP, expense, and card systems to read, understand, and make real-time decisions on spend data. - **Expense Audit Automation**: AI-driven auditing of employee expense reports to catch errors, fraud, and non-compliant expenses. - **Accounts Payable Automation**: End-to-end invoice processing, approval workflows, and duplicate payment prevention, covering the entire spend-to-pay process. - **Corporate Card Compliance**: Real-time monitoring and auditing of corporate card transactions to ensure policy compliance and reduce risk. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed (private company) - **Key Metric**: Total Funding – $280.6M across 7 rounds (Series D); Estimated Annual Revenue – $25.1M (per LinkedIn data) - **Notable Investors/Partners**: 500 Global, Resolute Ventures, Redpoint (led Series A); also integrates with SAP Concur, Oracle, NetSuite, and other major finance ecosystems - **Growth Signals**: - Trained on $50B+ in enterprise spend - One-third of the Fortune 500 are customers - 312 employees across 5 countries, with offices in the US, UK, and India - LinkedIn followers growth of +36.1% yearly, indicating rising brand awareness - Active hiring across AI engineering, implementation, and GTM roles (6 open positions at time of research) ## Competitive Advantages - **Patented AI purpose-built for finance**: Unlike generic automation tools, AppZen's AI is trained on massive enterprise spend data and understands the context of financial documents, continuously learning and adapting to each customer's unique needs. - **Full spend-to-pay coverage**: Handles everything from inbox management to invoice processing and expense auditing, reducing the need for multiple point solutions. - **Enterprise trust and scale**: With one-third of the Fortune 500 as customers and over a decade of domain expertise, AppZen has deep credibility in the finance automation market. - **Fully auditable and transparent**: AI decisions and outputs are designed to be auditable, which is critical for compliance-driven finance teams. - **Strong integration ecosystem**: Seamlessly works with existing AP, expense, and card workflows, including major ERPs and expense platforms. ## Strategic Focus - **Expanding agentic AI capabilities**: AppZen is building "agentic AI agents" for accounts payable and expense management, moving beyond simple automation toward autonomous decision-making. - **Enhancing the Mastermind platform**: Continuously adding new features and capabilities to redefine finance AI, with a focus on predicting issues, identifying opportunities, and optimizing workflows. - **Global growth and customer success**: Maintaining a strong presence in the US, UK, and India while deepening relationships with enterprise customers and scaling customer success operations. - **Talent acquisition in AI and engineering**: Actively hiring for AI engineers, backend developers (Golang), and integration specialists to support product innovation. ## Why Work Here - **Culture**: Emphasizes a "sustainable company where innovative minds create immediate impact in an engaging, collaborative atmosphere" – with values around inclusion, respect, empathy, and giving back to the community. - **Work model**: A mix of on-site and hybrid roles, with offices in San Jose (CA), Phoenix (AZ), Pune (India), and London (UK). Specific policies vary by role and location. - **Engineering culture**: Focus on solving complex AI challenges in finance, with opportunities to work on proprietary AI models, large-scale spend data, and integrations with major enterprise systems. - **Career development**: The company highlights that employees' ideas are valued, growth is supported, and team members are empowered to do their best work. - **Employee feedback**: Employer rating is 3.4/5 on LinkedIn (244 reviews), with culture rated 3.5 and compensation 3.6 – indicating a collaborative environment with competitive pay, though work-life balance scores slightly lower (3.2). - **Impact**: Opportunity to work on products used by one-third of the Fortune 500 and to shape the future of finance AI. ## Sources 1. [AppZen Careers](https://www.appzen.com/careers) 2. [AppZen About Us](https://www.appzen.com/about-us) 3. [AppZen Jobs on Lever](https://jobs.lever.co/appzen) 4. [AppZen LinkedIn](https://linkedin.com/company/appzen) 5. [CB Insights AppZen Profile](https://www.cbinsights.com/company/appzen) ## Other roles at AppZen, Inc. - [Implementation Success Manager - Expense](https://feeny.ai/job/implementation-success-manager-expense-appzen-inc-pune-z7ppmf4v2vae) — Pune, India - [Senior Product UX Designer](https://feeny.ai/job/senior-product-ux-designer-appzen-inc-san-jose-8aqdxgav0men) — San Jose, CA - [Senior IT Administrator (Global)](https://feeny.ai/job/senior-it-administrator-global-appzen-inc-pune-4tbv50ha0ebk) — Pune, India - [Senior Product Manager - B2B Payments](https://feeny.ai/job/senior-product-manager-b2b-payments-appzen-inc-san-jose-5w4xy9ya3vmv) — San Jose, CA - [Oracle Technical Manager](https://feeny.ai/job/oracle-technical-manager-appzen-inc-pune-0sy96qjrcgaj) — Pune, India - [Sales Development Representative - London (German-Speaking)](https://feeny.ai/job/sales-development-representative-london-german-speaking-appzen-inc-london-wdv56rbvnnpe) — London, United Kingdom - [Senior Revenue Accountant](https://feeny.ai/job/senior-revenue-accountant-appzen-inc-pune-w6gepnnxx3pn) — Pune, India - [Sr. Backend Developer ( Golang)](https://feeny.ai/job/sr-backend-developer-golang-appzen-inc-pune-esq004rezjv4) — Pune, India - [Senior Data Engineer](https://feeny.ai/job/senior-data-engineer-appzen-inc-pune-wpx87mv2grc7) — Pune, India - [Enterprise Account Executive - Germany](https://feeny.ai/job/enterprise-account-executive-germany-appzen-inc-germany-42j88dzf4zy0) — Germany