Software Engineer - AI Platform Services

Tekskills Inc.; Hyderabad; In loco; INR 3.500.000 - 7.000.000; Tempo pieno

Descrizione del lavoro

Tekskills Inc. is seeking an experienced Senior Platform Engineer to design, build, and operate core platform services powering internal AI/agentic capabilities.

You will own gateway concerns end-to-end, including routing, timeouts, streaming, multi-tenancy, and policy enforcement, while building MCP capabilities and ensuring scale on Kubernetes. The role requires 7+ years in software engineering, strong Python/Java/Go skills, distributed systems expertise, and production Kubernetes experience.

Competenze

• 7+ years of professional software engineering experience.
• Strong expertise in Python, Java, or Go with async patterns.
• Experience building high-throughput services and distributed systems.
• Production experience on Kubernetes with observability and tuning.
• Familiarity with LLM integration patterns and secure SDLC.

Mansioni

• Design, build, and operate core platform services powering internal capabilities.
• Own gateway/platform concerns end-to-end including routing, timeouts, and multi-tenancy.
• Build and operate MCP capabilities as part of the platform.
• Scale and ensure availability on Kubernetes with autoscaling and performance tuning.
• Raise reliability practices: SLOs/SLIs, incident response, and post-incident follow-ups.
• Improve delivery safety via CI/CD, IaC, and secure development practices.
• Influence roadmap and technical strategy to reduce platform risk.

Conoscenze

Python

Java

Go

Async patterns

Distributed systems

Kubernetes

Observability

System design leadership

Strumenti

Terraform

Datadog

OpenTelemetry

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).