Siddharth Matale

Senior Software and AI Backend Engineer with 6+ years of experience designing, developing, and deploying secure, production-grade microservices and event-driven architectures. Proven ability to design and deliver applications with practical systems design tradeoffs. Applied data science background with hands-on programming experience in Python and JavaScript.

Deep expertise in building and integrating applications with LLMs, vector databases, and model integration frameworks like LangChain and Model Context Protocol (MCP). Proficient in explaining and applying AI engineering practices (retrieval, context management, evaluation pipelines, MLOps patterns) to cross-functional engineering teams.

Lead AI Application Engineer at Arizona State University / Kognitico (2024-06 – Present)

• Design, deliver, test, and support production-grade Python applications, REST APIs, and event-driven microservices, applying practical systems design tradeoffs in Linux environments.
• Architect and implement LLM integrations using LangChain, MCP tools, and server integrations to orchestrate agentic AI workflows and multi-step reasoning capabilities.
• Design and run LLM evaluation pipelines combining quantitative and qualitative methods to balance precision-recall tradeoffs, align metrics with user workflows, and ensure grounding and low latency.
• Develop and deploy enterprise RAG solutions using vector databases (Pinecone), semantic retrieval, custom context management, guardrails, and structured retrieval approaches.
• Leverage PyTorch and the Hugging Face ecosystem (Transformers, Datasets) for lightweight model fine-tuning, evaluation, and rapid experimentation with emerging AI research.
• Apply AI engineering practices and MLOps patterns across teams while implementing observability, logging, and monitoring using Prometheus and Grafana for system reliability.

Senior Software and AI Backend Engineer at CRIF Financial Solutions (Oracle) (2022-02 – 2023-07)

• Designed and built secure, scalable RESTful APIs, microservices, and event-driven backend platforms using Python and Java in a highly regulated banking and financial services environment.
• Engineered messaging and event-streaming architectures using Kafka and MQ for high-throughput asynchronous processing and distributed systems design tradeoffs.
• Architected SQL and relational database solutions, optimizing queries, schema design, and structured retrieval across distributed data pipelines.
• Implemented Pydantic payload validations, column-level encryption, masking, and role-based access control following governance and security standards.
• Containerized cloud services using Docker and established CI/CD pipelines via GitHub Actions for automated zero-downtime releases.

Software Engineer at Neuromonk (2019-08 – 2022-01)

• Developed cloud-native microservices, REST APIs, and backend modules using Python, Java, SQL, and JavaScript, maintaining sub-500ms latency and 99.9% uptime.
• Participated in full SDLC lifecycle, collaborating across cross-functional engineering teams to translate technical findings into clear guidance and architecture.
• Contributed to test automation, CI/CD workflows using Docker and GitHub Actions, and applied core software engineering practices for maintainable code.

Master of Science in Computer Science (Applied Data Science / AI) – Arizona State University (2023-08 – 2025-05)

Bachelor of Engineering in Computer Engineering – Sinhgad Institute of Technology (2017-08 – 2021-07)