{"id":3936034,"url":"https://alion.io/job/comviva-senior-platform-engineer-core-platforms-ai","title":"Senior Platform Engineer - Core Platforms & AI","company":{"id":452675,"name":"Comviva","domain":"comviva.com","url":"https://alion.io/company/comviva","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Grafana","optional":true},{"name":"IAM","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Prometheus","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-08T07:35:15Z","employer_posted_date":null,"last_verified_at":"2026-11-08T07:35:15Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Key Responsibilities:\nDesign, build, and own reusable Core Platform capabilities that provide common building blocks for engineering teams across products and functions.\nTake ownership of platform initiatives end-to-end - from understanding the problem and designing the solution to implementation, deployment, monitoring, and ongoing production support.\nDesign and implement scalable, reliable services and APIs using modern software engineering and distributed-systems principles.\nModernize existing platform components, addressing technical debt and legacy patterns while improving scalability, reliability, maintainability, and developer experience.\nBuild and integrate AI-powered platform capabilities, including LLM applications, RAG pipelines, agentic workflows, model integrations, and AI-enabled services.\nPrototype new technologies and ideas quickly, validate them through working implementations, and take successful solutions toward production.\nMake pragmatic technical decisions around architecture, technology choices, design patterns, and build-vs-buy, while keeping long-term maintainability in mind.\nImprove platform performance, reliability, scalability, security, and observability across production systems.\nEstablish engineering practices and reusable patterns that enable teams to build consistently on the platform.\nWork closely with engineering, data science, product, and other stakeholders to understand requirements and translate them into robust technical solutions.\nTroubleshoot complex production issues and drive them through to resolution.\nAct as a technical owner and hands-on engineering leader for critical platform initiatives, without being limited to a specific product or functional area.\n\nMust-Have Technical Skills:\nStrong hands-on experience with Python or Java, with a track record of designing and building production-grade services, REST APIs, and microservices.\nStrong understanding of system design, distributed systems, scalability, reliability, and software engineering fundamentals.\nExperience with AWS or another major public cloud, along with Docker and Kubernetes.\nStrong experience with SQL and NoSQL databases and understanding of data access and persistence patterns.\nExperience with Git, CI/CD, automated testing, and production troubleshooting.\nExperience with messaging and event-streaming systems such as Kafka, Pulsar, or similar.\nHands-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.\nAbility to independently take a technical problem from problem definition -> design -> implementation -> deployment -> production ownership.\n\nGood To Have Skills:\nBroader exposure to the agentic AI ecosystem, including multiple frameworks, MCP or similar tool-integration patterns, prompt engineering, and model orchestration.\nExposure to data engineering technologies such as Spark, Airflow, or similar.\nExperience with observability and platform operations, including Prometheus, Grafana, OpenTelemetry, ELK, or similar.\nUnderstanding of IAM, security, and secure platform design.\nExposure to MLOps, model evaluation, AI guardrails, and AI observability.\nExperience deploying or managing open-source LLMs.\nExperience with fintech or other regulated, large-scale distributed systems.\nOpen-source contributions or active participation in the technical community.\n\nWhat We're Looking For:\nBuilder first: You enjoy writing production code and solving real engineering problems, not just producing design documents.\nEnd-to-end ownership: You are comfortable owning a problem from initial understanding through design, implementation, deployment, and production operation.\nStrong system thinker: You can reason about the larger platform while still diving deep into code and implementation details.\nPragmatic engineer: You make technology choices based on the problem, rather than chasing technology for its own sake.\nIndependent owner: Once the objective is clear, you can define the approach, drive execution, and make the necessary technical decisions.\nFast learner: You are comfortable evaluating emerging technologies and turning promising ideas into working prototypes and production capabilities.\nCollaborative technical leader: You can influence engineers and stakeholders through strong technical thinking, hands-on contribution, and clear communication.\nProduct and platform mindset: You build reusable capabilities that solve problems across multiple teams rather than one-off solutions for a single use case.\n\nWhy Join Us?:\nOwn and shape Core Platforms that are fundamental to our fintech products.\nTake ideas from concept and design all the way to production with significant technical ownership.\nWork on high-impact platform initiatives spanning cloud-native engineering, distributed systems, data, and AI.\nBuild real-world AI capabilities including LLM applications, RAG, agentic systems, and AI platform services.\nWork across multiple engineering and product areas, with the opportunity to influence how technology is built across the organization.\nJoin a team where hands-on engineering, ownership, and pragmatic technical decision-making are valued.\nSkills\nAWS, AutoGen, CrewAI, Docker, Java, Kubernetes, LLM, LangChain, LangGraph, 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