Software Engineer - AI Platform Services

Tekskills Inc.; Bengaluru; Presencial; INR 3.500.000 - 7.000.000; Jornada completa

Descripción de la vacante

Tekskills Inc. in Bengaluru, India seeks an experienced Platform Engineer to design, build, and operate core services powering internal AI capabilities.

You will own gateway concerns end-to-end, ensure scalable, reliable Kubernetes deployments, and contribute to strategy and security practices. The role requires leadership in architecture reviews and cross-team initiatives, with strong skills in Python/Java/Go, async patterns, and distributed systems.

Formación

• 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 communications skills able to translate technical tradeoffs to stakeholders and partner teams.]
• job_responsibilities_description:[

Responsabilidades

• Design, build, and operate core platform services powering firm-wide internal AI/agentic capabilities.
• Own gateway/platform concerns end-to-end: routing, timeouts/retries, streaming, rate limits, multi-tenancy, policy enforcement, provider abstraction, safe degradation, 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, production debugging.
• Raise reliability practices: SLOs/SLIs, instrumentation standards, incident response/runbooks, post-incident follow-ups, load/resilience testing, operational excellence.
• Improve delivery safety: CI/CD, environment promotion, IaC-driven repeatability, secure SDLC practices.
• Influence roadmap and technical strategy: prioritize foundational investments and reduce platform risk for a business-critical internal platform.

Conocimientos

Python

Java

Go

Async patterns

Concurrency

High-throughput services

FastAPI

Herramientas

Kubernetes

Terraform

Datadog

OpenTelemetry

CI/CD

Descripción del empleo

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).