Specialist - IT - Engineering

Overview

Backend Engineer who has built and run production systems at scale, owning services end-to-end and acting as a technical leader on the team.

What you'll do

• Design, build, and operate distributed microservices running on Kubernetes in AWS.
• Own services through their full lifecycle: architecture, coding, testing, deployment, on-call, and iteration based on production feedback.
• Design and evolve event-driven pipelines using Kafka (or similar streaming systems).
• Work across the AWS stack (EC2, RDS, S3, IAM, VPC, Lambda, ECS/EKS, CloudWatch, etc.) and make informed trade-offs on cost, scalability, and reliability.
• Use AI coding assistants and internal AI tooling to accelerate development, review, and debugging, and help the team adopt them effectively.
• Identify opportunities to apply AI/ML capabilities (e.g., LLM-based features, intelligent automation, agentic workflows) where they solve real product or engineering problems.
• Drive technical decisions on your team: propose designs, run design reviews, and push back constructively when needed.
• Mentor junior and mid-level engineers through code reviews, pairing, and design discussions.
• Take ownership of incidents, from detection through root-cause analysis and postmortems, and drive follow-through on action items.
• Partner with product, SRE/DevOps, and other engineering teams to plan and deliver roadmap work.

What you'll need

• 5+ years of professional backend software engineering experience.
• Strong experience designing and operating microservices architectures in production.
• Hands-on experience with Kubernetes (deployments, services, config/secrets management, autoscaling, load balancing, debugging pods/nodes in production).
• Proficiency with Apache Kafka or equivalent (event streaming, partitioning, consumer groups, schema management).
• Strong working knowledge of AWS: RDS, EC2, S3, IAM, VPC/networking basics, and at least one compute/orchestration service (ECS, EKS, or Lambda).
• Solid understanding of relational databases (schema design, indexing, query optimization, migrations), RDS/Postgres or MySQL preferred.
• Proficiency in at least one backend language commonly used (e.g., Java, Go, Python, Node.js).
• Understanding of API design (REST and/or gRPC), authentication/authorization patterns, and API versioning.
• Practical experience with observability: structured logging, metrics, and distributed tracing (e.g., CloudWatch, Prometheus/Grafana, Datadog, Open Telemetry).
• Comfort with asynchronous, event-driven, and eventually-consistent system design.
• Basic understanding of CI/CD pipelines and Infrastructure as Code (Terraform, CloudFormation, or similar).
• Security fundamentals: secrets management, least-privilege IAM, dependency/vulnerability scanning and remediation.
• Demonstrated ownership: has driven a project or service from design through production and long-term maintenance.
• Has taken point on a production incident: led triage, communicated status, and driven the postmortem/fix.
• Regular hands-on use of AI coding assistants (e.g., Kiro, GitHub Copilot, Claude Code, Cursor) in real development workflows.
• Working understanding of core AI/LLM concepts: prompting, embeddings, RAG, tool use/function calling, and agentic workflows, enough to evaluate where they add value and where they don't.
• Judgment about AI tool limitations and knows when to trust AI-generated code vs. when to verify manually, especially around security, correctness, and data handling.

Nice to have

• Experience in migrating workloads to Cloud, DB migrations, etc.
• Experience with service mesh (Istio/Gloo), API gateways, or multi-region/multi-AZ architectures.
• Exposure to cost optimization / FinOps practices in AWS.
• Experience with NoSQL stores (DynamoDB, Redis, Elasticsearch/OpenSearch) alongside RDS.
• Experience building or integrating with LLM-based features in production.

Details

• Location: Bangalore, Karnātaka, India.