2 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Write production-quality code across core services, platforms, and AI workflows.
- Own high-impact features and complete project workstreams from discovery and solution design through launch and post-launch improvement.
- Design and build scalable microservices, APIs, event-driven integrations, SaaS applications, and cloud-native systems.
- Lead modernization of legacy systems and incremental migration to modern architectures.
- Build and orchestrate agentic AI systems with tool use, multi-step reasoning, workflow automation, planning, memory, guardrails, and human oversight.
- Integrate AI systems with business workflows, APIs, data sources, datastores, and event-driven systems.
- Implement grounding, retrieval, validation, structured outputs, monitoring, evaluation, and feedback loops for production AI behavior.
- Set architectural standards, guide service boundaries and integration patterns, and make tradeoffs involving speed, scalability, correctness, reliability, and cost.
- Establish practices and guardrails for AI-assisted development and use tools for design, refactoring, testing, debugging, documentation, and delivery acceleration.
- Provide technical leadership across teams, manage dependencies and risks, align stakeholders, and serve as an escalation point for difficult distributed-systems, data, and AI problems.
- Mentor engineers through pairing, code reviews, design discussions, and coaching toward broader technical leadership.
- Build containerized applications, support CI/CD, observability, safe deployments, testing, deployment, and production operations.
Requirements
- 10+ years of professional software development experience.
- Proven ownership and delivery of large, complex systems, including successful legacy modernization.
- Hands-on experience designing, building, and shipping AI-driven and agentic AI systems in production or production-like environments.
- History of hands-on technical leadership across teams or domains, mentoring engineers, coordinating stakeholders, managing risks, and independently driving projects through delivery.
- Expert-level proficiency in C# and .NET, including ASP.NET Core and modern .NET.
- Deep understanding of distributed systems, RESTful API design, and microservices architectures.
- Hands-on experience with LLMs, agentic AI architectures, autonomous workflow execution, tool or function calling, context and memory management, and AI workflow orchestration such as MCP-style patterns.
- Experience integrating AI systems with datastores, APIs, and event-driven workflows.
- Experience with relational databases including SQL Server and PostgreSQL, plus working knowledge of NoSQL data stores and caching strategies such as Redis.
- Strong experience with Docker and production containerization, plus practical Kubernetes and container-orchestration experience.
- Comfort working in AWS and/or Azure cloud environments.
- Proficiency with Git and modern development workflows, along with strong testing-strategy and production-code knowledge.
- Bachelor’s degree in computer science or equivalent practical experience.
- Preferred qualifications include Java or polyglot-environment experience, Kafka, RabbitMQ, ActiveMQ, distributed caching, React, Angular, Vue, high-throughput or real-time AI systems, AI safety or governance frameworks, and Agile/Scrum experience.
Tech Stack
AngularApache KafkaAWSAzureC#DockerGitKubernetesMicrosoft SQL Server.NETPostgreSQLRabbitMQReactRedisVue.js
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