Key Responsibilities

- Design, build, and own reusable Core Platform capabilities that provide common building blocks for engineering teams across products and functions.
- Take ownership of platform initiatives end-to-end — from understanding the problem and designing the solution to implementation, deployment, monitoring, and ongoing production support.
- Design and implement scalable, reliable services and APIs using modern software engineering and distributed-systems principles.
- Modernize existing platform components, addressing technical debt and legacy patterns while improving scalability, reliability, maintainability, and developer experience.
- Build and integrate AI-powered platform capabilities, including LLM applications, RAG pipelines, agentic workflows, model integrations, and AI-enabled services.
- Prototype new technologies and ideas quickly, validate them through working implementations, and take successful solutions toward production.
- Make pragmatic technical decisions around architecture, technology choices, design patterns, and build-vs-buy, while keeping long-term maintainability in mind.
- Improve platform performance, reliability, scalability, security, and observability across production systems.
- Establish engineering practices and reusable patterns that enable teams to build consistently on the platform.
- Work closely with engineering, data science, product, and other stakeholders to understand requirements and translate them into robust technical solutions.
- Troubleshoot complex production issues and drive them through to resolution.
- Act as a technical owner and hands-on engineering leader for critical platform initiatives, without being limited to a specific product or functional area.

Must-Have Technical Skills

- Solid hands-on experience with Python or Java, with a track record of designing and building production-grade services, REST APIs, and microservices.




- Strong understanding of system design, distributed systems, scalability, reliability, and software engineering fundamentals.
- Experience with AWS or another major public cloud, along with Docker and Kubernetes.
- Strong experience with SQL and NoSQL databases and understanding of data access and persistence patterns.
- Experience with Git, CI/CD, automated testing, and production troubleshooting.
- Experience with messaging and event-streaming systems such as Kafka, Pulsar, or similar.
- Hands-on experience building and deploying at least one LLM-powered application, such as a RAG or agentic application, using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
- Ability to independently take a technical problem from problem definition → design → implementation → deployment → production ownership.

Good To Have Skills

- Broader exposure to the agentic AI ecosystem, including multiple frameworks, MCP or similar tool-integration patterns, prompt engineering, and model orchestration.
- Exposure to data engineering technologies such as Spark, Airflow, or similar.
- Experience with observability and platform operations, including Prometheus, Grafana, OpenTelemetry, ELK, or similar.
- Understanding of IAM, security, and secure platform design.
- Exposure to MLOps, model evaluation, AI guardrails, and AI observability.
- Experience deploying or managing open-source LLMs.
- Experience with fintech or other regulated, large-scale distributed systems.




- Open-source contributions or active participation in the technical community.

What We're Looking For

- Builder first: You enjoy writing production code and solving real engineering problems, not just producing design documents.
- End-to-end ownership: You are comfortable owning a problem from initial understanding through design, implementation, deployment, and production operation.
- Strong system thinker: You can reason about the larger platform while still diving deep into code and implementation details.
- Pragmatic engineer: You make technology choices based on the problem, rather than chasing technology for its own sake.
- Independent owner: Once the objective is clear, you can define the approach, drive execution, and make the necessary technical decisions.
- Fast learner: You are comfortable evaluating emerging technologies and turning promising ideas into working prototypes and production capabilities.
- Collaborative technical leader: You can influence engineers and stakeholders through strong technical thinking, hands-on contribution, and clear communication.
- Product and platform mindset: You build reusable capabilities that solve problems across multiple teams rather than one-off solutions for a single use case.

Why Join Us?

- Own and shape Core Platforms that are fundamental to our fintech products.
- Take ideas from concept and design all the way to production with significant technical ownership.
- Work on high-impact platform initiatives spanning cloud-native engineering, distributed systems, data, and AI.
- Build real-world AI capabilities including LLM applications, RAG, agentic systems, and AI platform services.
- Work across multiple engineering and product areas, with the opportunity to influence how technology is built across the organization.
- Join a team where hands-on engineering, ownership, and pragmatic technical decision-making are valued.

📌 Senior Platform Engineer - Core Platforms & AI (Gurugram)
🏢 Comviva
📍 Gurugram