Software Engineer - AI Platform Services

Tekskills Inc.; Chennai; In loco; INR 3.000.000 - 6.000.000; Tempo pieno

Descrizione del lavoro

Tekskills Inc. is seeking an experienced senior software engineer to design, build and operate core platform services powering internal AI capabilities. You will own gateway concerns end-to-end and ensure robust, scalable Kubernetes-based deployments.

The role emphasizes leadership in architectural decisions, async patterns, and collaboration across teams to reduce platform risk and improve reliability. Strong communication is essential.

Competenze

• 7+ years of professional software engineering experience
• Strong expertise in Python, Java, or Go including async patterns, concurrency
• Solid distributed systems fundamentals: idempotency, backpressure, rate limiting
• Production experience operating services on Kubernetes
• Basic familiarity with LLM integration patterns
• Demonstrated design leadership (RFCs, architecture reviews)
• Excellent communication translating technical tradeoffs to stakeholders

Mansioni

• Design, build, and operate core platform services (Python; REST + async; streaming where appropriate)
• Own gateway/platform concerns end-to-end: routing, timeouts/retries, streaming, rate limits/quotas, multi-tenancy
• Build and operate MCP capabilities as part of the platform
• Scale and availability on Kubernetes: autoscaling, rollout strategies, performance tuning
• Raise reliability practices: SLOs/SLIs, instrumentation, incident response, post-incident follow-ups
• Improve delivery safety: CI/CD, IaC-driven repeatability, secure SDLC practices
• Influence roadmap and technical strategy: reduce platform risk for internal platform

Conoscenze

Python

Java

Go

Async patterns

High-throughput services

Distributed systems

Communication

Strumenti

Kubernetes

AWS/GCP/Azure

Datadog/OpenTelemetry

Terraform

Descrizione del lavoro

Key Responsibilities

• Design, build, and operate core platform services (Python; REST + async; streaming where appropriate) powering firm-wide internal AI/agentic capabilities.
• Own gateway/platform concerns end-to-end: routing, timeouts/retries, streaming, request shaping, rate limits/quotas, multi-tenancy, policy enforcement, provider abstraction, safe degradation, and robust client experience.
• Build and operate MCP capabilities as part of the platform.
• Build for scale and availability on Kubernetes: autoscaling, rollout strategies, capacity planning, performance tuning, and production debugging.
• Raise reliability practices: define and manage SLOs/SLIs, instrumentation standards, incident response/runbooks, post-incident follow-ups, load/resilience testing, and operational excellence.
• Improve delivery safety: CI/CD, environment promotion, IaC-driven repeatability, and secure SDLC practices.
• Influence roadmap and technical strategy: prioritize foundational investments and reduce platform risk for a business-critical internal platform.

Required Qualifications

• 7+ years of professional software engineering experience (or equivalent practical experience)
• Strong expertise in Python, Java, or Go, including async patterns, concurrency, and building high-throughput services (FastAPI or similar).
• Solid distributed systems fundamentals: idempotency, backpressure, failure isolation, consistency tradeoffs, rate limiting, retries/timeouts.
• Production experience operating services on Kubernetes (deployments, autoscaling, debugging, observability, performance).
• Basic familiarity with LLM integration patterns (streaming responses, tool/function calling)
• Demonstrated design leadership (RFCs, architecture reviews, leading cross-team initiatives).
• Excellent communication skillsable to translate technical tradeoffs to stakeholders and partner teams.

Preferred Qualifications

• Experience with service-to-service authentication patterns (API keys, OAuth/JWT, mTLS concepts).
• Familiarity with observability tooling (structured logs, metrics, tracing; Datadog or OpenTelemetry a plus).
• Strong fundamentals in AWS (or GCP/Azure) relevant to secure platforms (IAM, networking basics, compute, logging/monitoring patterns).
• Working proficiency with Terraform and automation-first operations (repeatable environments, policy checks, safe rollouts).
• Comfort using AI dev tools (Claude Code, Cursor, Gemini CLI) responsibly (tests, validation, secure coding).