We are hiring a Sr Software Engineer, AI-Native Operations Platform to technically own and scale GameKit Assistant and the broader AI operations platform.
This is a global technical leadership role based in India.
The Sr Software Engineer will own architecture, engineering standards, roadmap sequencing, technical delivery outcomes, and mentorship across globally distributed teams.
We seek a seasoned, hands-on technical lead with a background in architecting high-scale backend environments and complex distributed systems. You possess direct production experience with Generative AI and understand that an effective assistant demands more than precision—it must be performant, user-centric, secure, and built upon a foundation of operational trust.
Key Responsibilities
Own the architecture and technical roadmap for GameKit Assistant and EA’s AI-native operations platform.
Build scalable platform capabilities across conversational support, knowledge operations, workflow automation, incident orchestration, evaluation, and service intelligence.
Improve the Slack assistant experience so responses are concise, contextual, actionable, and low-noise.
Lead production AI capabilities including RAG, hybrid search, LLM evaluation, prompt/version management, guardrails, observability, and hallucination detection.
Design reliable backend systems and integrations across Slack, Jira, PagerDuty, GitLab, Perforce, Shift, JaaS, TestRail, Grafana, AKS, PostgreSQL, and Azure AI services.
Establish engineering standards for architecture, service reliability, action safety, observability, release quality, and incident readiness.
Mentor engineers through design reviews, code reviews, debugging, technical guidance, and hands-on leadership.
Convert operational friction, support patterns, and platform signals into reusable automation and intelligence capabilities.
Required Qualifications
15+ years of software engineering experience building and operating large-scale backend platforms, distributed systems, developer platforms, automation platforms, or enterprise internal tools.
Strong hands-on engineering experience in Python, Java, Go, Scala, or similar backend languages. Python experience is preferred.
Practical production experience with Generative AI, RAG, LLM integrations, vector search, evaluation pipelines, guardrails, observability, and AI-enabled workflow automation.
Deep experience with Kubernetes, APIs, event-driven systems, queues, databases, caching, CI/CD, telemetry, distributed tracing, and production operations.
Strong understanding of reliability patterns such as retries, idempotency, rate limits, circuit breakers, async processing, failure isolation, rollout safety, and incident response.
Experience designing integrations across enterprise platforms with strong attention to identity, permissions, auditability, security, operational safety, and user impact.
Ability to influence technical direction, mentor engineers, review complex designs, challenge weak assumptions, and drive delivery across globally distributed teams.
Excellent technical writing, communication, and stakeholder influence skills.
Master’s degree or a Doctorate in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Preferred Qualifications
Experience in platform engineering, developer productivity, SRE, cloud infrastructure, enterprise automation, internal developer platforms, payments, large-scale SaaS, or high-throughput consumer technology environments.
Experience building AI-enabled support systems, workflow orchestration platforms, incident response tooling, knowledge platforms, service intelligence capabilities, or developer-facing assistants.
Experience with Slack apps, conversational UX, support automation, ticketing workflows, incident workflows, human-in-the-loop systems, or action-based assistants.
Experience with Azure, AKS, Azure OpenAI, Azure AI Search, Azure Blob Storage, PostgreSQL, Grafana, ArgoCD, GitLab, PagerDuty, or similar enterprise platform technologies.
Experience working with globally distributed engineering teams across India, North America, and Europe.
Strong ability to simplify complex systems, challenge weak designs, and mentor engineers without becoming a bottleneck.