{"id":3152873,"url":"https://alion.io/job/egen-principal-aiml-architect","title":"Principal AI/ML Architect","company":{"id":11725,"name":"Egen","domain":"egen.ai","url":"https://alion.io/company/egen","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":90,"open_postings":5,"ghost_share":0,"stale_share":0.4,"repost_share":0,"time_to_fill_p50_days":46,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","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":24000,"max_usd":62000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Google ADK","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Hybrid Search","optional":false},{"name":"IAM","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Vertex AI","optional":false},{"name":"Kubernetes","optional":true},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-10-23T09:21:05Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-27T21:19:28Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About Egen:\nEgen is a fast-growing, entrepreneurial technology company with a data-first mindset. We bring together exceptional engineering talent and advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights.\nWe are committed to being a place where talented people choose to do their best work - applying deep engineering and technology expertise to envision how data, AI, and platforms can change the world for the better. We are dedicated to learning, thrive on solving difficult problems, and continually innovate to achieve fast, effective results. If that describes you, we want you on our team.\nAbout the opportunity:\nAs a Principal AI/ML Architect, you will set the technical direction for Egen's most complex generative AI, agentic AI, and applied machine learning engagements while remaining personally hands-on in the work that matters most. We treat AI as a software engineering discipline. You will raise that bar by architecting systems that succeed in production and helping the engineers around you do the same.\nYou will own the hardest architectural problems in our portfolio: agentic platforms operating at scale, applied-ML solutions, advanced retrieval systems, and AI in regulated or high-stakes environments where being wrong is expensive. Document intelligence and RAG pipelines are part of your toolkit, not the ceiling. You will take systems from an ambiguous business problem to a robust, scalable service, solving for latency, reliability, cost, security, and governance.\nYou will also be the senior technical face of our engagements. You will partner directly with client leadership to translate business strategy into AI architecture, shape solutions during pre-sales, guide engineering teams, and earn the trust that turns a project into a long-term program.\nWhat you will do:\nSet enterprise AI architecture and technical direction: Own the end-to-end architecture for complex GenAI, agentic AI, and ML platforms. Define reference architectures, reusable patterns, engineering guardrails, and technology choices across engagements.\n\nBuild at the frontier - hands-on: Stay close to the code on the highest-leverage technical work, including foundation-model and embedding fine-tuning, advanced RAG, semantic search, evaluation harnesses, and novel agentic workflows using Python and Google Cloud Vertex AI.\n\nEngineer AI for production: Design for latency, reliability, security, cost, scalability, and maintainability from day one. Apply disciplined MLOps and LLMOps practices so systems are versioned, evaluated, monitored, deployed, and continuously improved.\n\nArchitect agentic systems at scale: Design and operate multi-step reasoning and multi-agent workflows using ADK, LangChain, MCP, and custom agent frameworks, with robust orchestration, state management, tool use, memory, human oversight, failure isolation, and verification controls.\n\nEstablish evaluation, observability, and responsible AI standards: Define measurable quality criteria and production telemetry for accuracy, groundedness, safety, drift, latency, and cost. Embed privacy, security, governance, and responsible AI throughout the lifecycle.\n\nShape data and retrieval architectures: Design production-scale retrieval and knowledge systems spanning data ingestion, chunking, metadata, embeddings, vector and hybrid search, re-ranking, provenance, permissions, and continuous content refresh.\n\nAdvise clients and shape opportunities: Partner with client executives and engineering leaders to translate business strategy into AI roadmaps and solution architectures. Lead discovery, technical workshops, estimates, trade-off discussions, and pre-sales solutioning.\n\nMultiply engineering capability: Raise the technical bar through architecture reviews, design documents, code reviews, mentoring, reusable accelerators, and clear standards that help senior and mid-level engineers deliver with greater confidence.\n\nOwn outcomes across the full lifecycle: Guide initiatives from problem framing and experimentation through production rollout, operational readiness, adoption, and measurable business value. Surface risks early and drive decisions to resolution.\n\nYour technical toolkit:\nLanguages and software engineering\nExpert-level Python; strong shell scripting; API and service design; clean, tested, maintainable code; distributed-system fundamentals; and full SDLC ownership.\nModels and AI ecosystem\nDeep, current expertise with Google Gemini, GPT-class models, LLaMA and other open models; advanced prompt engineering; structured outputs; model selection; fine-tuning; and rigorous evaluation.\nAgentic AI engineering\nHands-on production experience with Google Agent Development Kit (ADK), LangChain, custom agent frameworks, tool use, Model Context Protocol (MCP), workflow orchestration, planning, memory, state, guardrails, human-in-the-loop controls, and multi-agent design.\nRetrieval and search\nAdvanced RAG, hybrid and semantic search, embeddings, re-ranking, and vector platforms such as Vertex AI Vector Search, pgvector, Pinecone, or equivalent technologies.\nCloud infrastructure and AI systems\nEnd-to-end experience architecting highly available, scalable AI and software environments across Google Cloud / Vertex AI, AWS, and Azure, including model serving, data integration, IAM, networking, security, observability, and cost management.\nFrameworks\nStrong command of LangChain, LlamaIndex, or equivalent orchestration layers - together with the judgment to use simpler, more maintainable patterns when appropriate.\nMLOps and LLMOps\nCI/CD, model and prompt versioning, experiment tracking, automated evaluation, observability, model monitoring, drift detection, rollback, and production incident response.\nData and ML foundations\nStrong SQL and data engineering; classical machine learning; neural networks; training, tuning, and inference; and the ability to connect data quality to model and product outcomes.\nBasic qualifications:\nBachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field; equivalent practical experience will also be considered.\n\n15+ years of progressive experience across software engineering, machine learning, data, or AI, including substantial ownership of production systems at scale.\n\nDemonstrated principal-level technical leadership, including architecture ownership, cross-team technical direction, and decision-making across complex engagements or product portfolios.\n\nA proven record of deploying generative AI, agentic AI, and/or applied-ML products into production - beyond proofs of concept.\n\nDeep hands-on expertise with Python, modern LLM and ML architectures, agent frameworks, Google Cloud / Vertex AI, production APIs, and scalable software systems.\n\nExperience establishing evaluation, observability, security, privacy, governance, and responsible AI controls for enterprise AI solutions.\n\nStrong data engineering and SQL knowledge, with the ability to design reliable data and retrieval foundations for AI products.\n\nSenior client-facing experience, with the communication skills to explain technical choices, risks, and business value to executive stakeholders and engineering teams.\n\nPreferred qualifications:\nExperience training, tuning, or adapting neural networks, embedding models, or foundation models.\n\nArchitecture experience in regulated or high-stakes domains such as healthcare, financial services, or the public sector.\n\nGoogle Cloud Professional Machine Learning Engineer, Professional Cloud Architect, or comparable certification.\n\nExperience building reusable AI accelerators, reference implementations, or platform capabilities across multiple clients or product teams.\n\nPre-sales experience including discovery workshops, solution shaping, estimation, proposal development, and technical presentations.\n\nFamiliarity or good to have understanding with Kubernetes, infrastructure as code, event-driven architectures, and modern data platforms.","description_format":"text","description_chars":8046,"description_truncated":false,"requirements":{"experience_years_min":15,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","AI Consulting & Integration","Cloud Consulting & Migration","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-10-23T13:17:09Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":46,"reasons":["conf:2","velocity","win:early"],"computed_at":"2026-10-27T05:46:45Z"},"pay":null,"html_url":"https://alion.io/job/egen-principal-aiml-architect","json_url":"https://alion.io/job/egen-principal-aiml-architect.json","meta":{"generated_at":"2026-10-27T23:11:57Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":15132,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-28T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":11725},"rest":"https://alion.io/mcp/rest/get_company?id=11725"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fegen-principal-aiml-architect"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fegen-principal-aiml-architect"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fegen-principal-aiml-architect"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/egen-principal-aiml-architect\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fegen-principal-aiml-architect"}]}