{"id":1285459,"url":"https://alion.io/job/technogen-platform-engineer","title":"Platform Engineer","company":{"id":3800111,"name":"TechnoGen","domain":"technogenindia.com","url":"https://alion.io/company/technogen","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":11000,"max_usd":30000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":15},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"FinOps","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"GitOps","optional":false},{"name":"ISO 27001","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Pulumi","optional":false},{"name":"SOC 2","optional":false},{"name":"Terraform","optional":false},{"name":"Ray","optional":true},{"name":"Ray Serve","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-08-14T07:46:57Z","employer_posted_date":null,"last_verified_at":"2026-08-14T07:46:57Z","board_verified":false,"closed_at":null,"days_open":48,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":48},"description":"Key Responsibilities:\n\n- Design & Build Cloud Platforms: Architect and implement scalable, secure, highly available cloud-native platforms across AWS, GCP, or Azure, including Kubernetes, networking, identity, and multi-tenancy.\n\n- Lead Platform Engineering Initiatives: Own complex, multi-month platform projects end-to-end, from architecture and technical design through implementation, production rollout, and continuous improvement.\n\n- Develop Internal Developer Platforms (IDP): Build and enhance self-service platforms, tooling, and workflows that improve developer productivity, standardisation, and overall developer experience.\n\n- Drive Infrastructure as Code & GitOps: Establish and standardise infrastructure and deployment practices using tools such as Terraform/Pulumi and ArgoCD across engineering teams.\n\n- Build AI/ML Infrastructure: Design and operate infrastructure supporting model serving, inference pipelines, GPU workloads, and LLM integrations, ensuring scalability, reliability, and performance.\n\n- Ensure Security & Compliance: Embed security, governance, and compliance best practices across the platform, aligning infrastructure with frameworks such as SOC 2, ISO 27001, and GDPR.\n\n- Optimise Platform Cost & Performance: Drive FinOps initiatives and optimise cloud/GPU resource utilisation, particularly for large-scale AI/ML and inference workloads.\n\n- Technical Leadership & Documentation: Create design documents and ADRs, communicate architectural decisions clearly, manage technical risks, and collaborate with engineering and business stakeholders to establish long-term platform strategy.\n\nRequirements:\n\n- 5 to 8 years in platform, infrastructure, or SRE with at least 3 years focused on cloud infrastructure or developer platforms.\n\n- Expertise in cloud-native architecture: Kubernetes at scale, managed cloud services, networking, identity federation, and multi-tenancy patterns across AWS, GCP, or Azure.\n\n- Proven ownership of complex, multi-month platform initiatives youve been part of them from whiteboard to production, managing ambiguity and technical risk throughout.\n\n- Proficient in IaC and GitOps fluency Terraform or Pulumi, ArgoCD with experience standardising platform tooling and deployment patterns across engineering teams.\n\n- Hands-on experience with AI/ML infrastructure: model serving, inference pipelines, GPU resource management, or LLM integration patterns.\n\n- Experience in enterprise environments with familiarity with compliance frameworks such as SOC 2, ISO 27001, or GDPR.\n\n- Strong written communication you write clear design docs, maintain useful ADRs, and can explain architectural decisions to both engineers and non-technical stakeholders.\n\nNice to Have:\n\n- You treat platform as a product and obsess over internal developer experience.\n\n- FinOps or GPU cost optimisation across large inference workloads.\n\n- You default to writing things down and creating shared technical context.\n\n- Building an internal developer platform (IDP) from scratch.\n\n- LLM serving at scale vLLM, Triton, Ray Serve or AI gateway design patterns.\n\n- You push back on short-term thinking and advocate for the right long-term call.\n\n- Open-source contributions to platform or ML infrastructure tooling.\n\n- Youre energised by ambiguity and build clarity where there isnt any.\nSkills\nDevOps, Kubernetes, AWS, Terraform, Azure, Google Cloud Platform, Cloud Services, IT Infrastructure Automation, Site Reliability, Cloud Infrastructure","description_format":"text","description_chars":3480,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Outsourcing & Dedicated Teams"],"lifecycle":[{"event":"open","at":"2026-09-26T04:00:00Z"}],"liveness":{"score":7,"band":"cold","label":"Long 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