{"id":1999568,"url":"https://alion.io/job/trianz-principal-ai-architect","title":"Principal AI Architect","company":{"id":2613198,"name":"Trianz","domain":"trianz.com","url":"https://alion.io/company/trianz","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":25000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":44},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EKS","optional":false},{"name":"AWQ","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"GCP","optional":false},{"name":"GGUF","optional":false},{"name":"Google GKE","optional":false},{"name":"GPTQ","optional":false},{"name":"Kubernetes","optional":false},{"name":"Llama","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Mistral","optional":false},{"name":"OpenShift","optional":false},{"name":"Quantization","optional":false},{"name":"Qwen","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"VMWare","optional":false},{"name":"AI Agents","optional":true},{"name":"FinOps","optional":true},{"name":"OpenVINO","optional":true},{"name":"ROCm","optional":true},{"name":"SGLang","optional":true},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-10-07T10:26:25Z","employer_posted_date":null,"last_verified_at":"2026-10-07T10:26:25Z","board_verified":false,"closed_at":null,"days_open":15,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":15},"description":"ABOUT THIS ROLE.\n\n You will own the complete architecture for private and sovereign AI deployment at Trianz.\n\n This is not a cloud-API-consumption role.\n\n You will design the system that runs large language models inside customer environments -choosing the right models, designing the serving topology, setting CPU and GPU routing policies, and ensuring the entire stack is secure, sovereign, and provider-agnostic.\n\n This is a pure IC role with architectural authority over how AI runs in production.\n\n WHAT YOU WILL DO.\n\n Design the complete private LLM serving architecture: model selection, serving framework (vLLM,TensorRT-LLM, Triton), and runtime topology.\n\n Define intelligent CPU vs GPU routing policies: which model sizes and prompt types route to which compute tier based on latency, cost, and throughput targets.\n\n Architect multi-cloud model serving: AWS, Azure, GCP -provider-agnostic, no managed AI lock-in.\n\n Design on-premises serving for enterprise customers: RedHat OpenShift, VMware -containerised model serving on customer hardware.\n\n Architect per-tenant model isolation, data-residency compliance, and air-gapped sovereign deployment patterns.\n\n Define the release architecture for model versions: rollout, staged deployment, rollback, and promotion gates.\n\n Design the LLM governance framework: model behaviour monitoring, inference audit logging, guardrail architecture.\n\n Design the DevSecOps pipeline architecture and self-service deployment automation standards.\n\n Evaluate open-source models (Llama, Mistral, Qwen, Phi) against closed models for specific enterprise use cases.\n\n Produce architecture sign-off documents and review all AI system designs before implementation.\n\n MUST HAVE.\n\n Deployed LLMs to production in a real enterprise environment -not just API consumption.\n\n Hands-on with vLLM, TensorRT-LLM, or Triton in a production serving context.\n\n Designed CPU cluster inference (Intel Xeon / AMD EPYC) for open-source models.\n\n Kubernetes at production scale (EKS, AKS, GKE, or OpenShift) -not just local k8s.\n\n Designed multi-cloud, provider-agnostic AI architectures.\n\n Experience with model quantization (GPTQ, AWQ, GGUF) and routing trade-offs.\n\n 8+ years in AI/software architecture with at least 3 years in production LLM systems.\n\n GOOD TO HAVE.\n\n Experience with RedHat OpenShift for on-premises model serving.\n\n Familiarity with NVIDIA Dynamo, SGLang, or custom inference schedulers.\n\n GPU FinOps -cost modelling for mixed CPU/GPU inference fleets.\n\n Sovereign AI or regulated-industry deployment experience.\n\n Intel OpenVINO or AMD ROCm for CPU-optimised inference.\n\n Company Overview.\n\n Trianz is an applied AI solutions company that accelerates customer business transformation through AI powered \"Transformation Services as a Software Model\".\n\n With 25+ years of transforming enterprises, we've evolved to a product-led, platform-driven organization serving global enterprises across Financial Services, Insurance, Healthcare, Hi-Tech, Manufacturing, and other industries.\n\n With global presence across 4 continents, our platform portfolio under the unified Concierto brand delivers end-to-end transformations including solutions for Migrate, Manage, Maximize, Modernize, Insights & Agentic AI, and SecOps delivered through strategic partnerships with leading hyperscalers.\n\n We're building the premier innovation-led organization in the digital transformation space through AI-first methodologies and data-driven excellence RevolutionAIzing Transformations.\n\n- - \nSkills\nAI Architecture, Artificial Intelligence","description_format":"text","description_chars":3566,"description_truncated":false,"requirements":{"experience_years_min":8,"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":["Artificial Intelligence","LLM & Generative AI","Predictive Analytics"],"lifecycle":[{"event":"open","at":"2026-10-07T10:29:00Z"}],"visa":[],"liveness":{"score":66,"band":"ok","label":"Likely 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