{"id":116777,"url":"https://alion.io/job/mactores-generative-ai-forward-deployed-engineer","title":"Generative AI Forward Deployed Engineer","company":{"id":6938,"name":"Mactores","domain":"mactores.com","url":"https://alion.io/company/mactores","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"D","score":52,"open_postings":31,"ghost_share":0.71,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":87,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":8},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Aurora","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Strands Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"DPO","optional":false},{"name":"DynamoDB","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"HIPAA","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LoRA","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"PCI DSS","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"RLHF","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":".NET","optional":true},{"name":"Apache Kafka","optional":true},{"name":"C#","optional":true},{"name":"C++","optional":true},{"name":"Java","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"LangChain","optional":true},{"name":"Machine Learning","optional":true},{"name":"PEFT","optional":true},{"name":"Rust","optional":true},{"name":"SOC 2","optional":true}],"status":"live","first_seen_at":"2024-10-24T07:33:09Z","employer_posted_date":"2024-10-24","last_verified_at":"2026-10-16T10:55:14Z","board_verified":true,"closed_at":null,"days_open":722,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":721},"description":"Forward-deployed engineers (FDEs) are Mactores' services layer. You embed with the customer's team, own outcomes from discovery through the production cutover, and personally carry the delivery commitment.\nThe agent platform we deploy absorbs 60-70% of engagement work, discovery, assessment, design, and testing. You absorb the judgment: target architecture, refactoring trade-offs, model selection, cutover strategy, and the decisions an agent platform cannot make. The agent absorbs scale. You absorb judgment.\nThis is not a staff-augmentation seat and not an advisory role. You ship.\nWhat you will do?\nDeliver production agentic AI systems and AWS modernization engagements on committed dates across three pillars: Data Platform Modernization, Application & Database Modernization, and AI Agents for Apps.\nBuild and productionize AI agents, orchestration, retrieval pipelines, evaluation harnesses, observability running against real customer data, not demo data.\nConvert existing products into agents: expose product functionality as callable tools for agent-to-agent composition, or replace form-and-click UX with agent-native, intent-driven interfaces.\nConvert existing Business processes into agents: expose process functionality as callable tools for agent-to-agent composition, or replace form-and-click UX with agent-native, intent-driven interfaces.\nEmbed directly with customer engineering teams. Run architecture sessions, defend design decisions, and align stakeholders from VP Engineering to CTO.\nMake agent decisions traceable and defensible, validation runs in parallel with live workloads, and outputs hold up to internal audit and regulators (HIPAA, PCI-DSS, FSI-grade governance where the vertical demands it).\nFeed field experience back into the platform and practice: your deployment patterns, integration playbooks, and edge cases shape how we deliver.\nWhat are we looking for?\n Excellent communication skills (English) - verbal and written. Non-negotiable. You will present architecture to customer CTOs, write documents that hold up in audit, and defend judgment calls in the room.If you can build but not explain, this role is not a fit.\nYou have shipped production agentic AI systems on AWS. Not POCs, not notebooks - systems running in production for real users. This is the primary qualification. Be prepared to walk through what you shipped, the decisions you made, and what broke.\n Deep understanding of agentic architecture - you can design an agent system from first principles and explain why each component exists:\nAgent design patterns: single-agent vs. multi-agent systems, supervisor/orchestrator patterns, hierarchical agent topologies, planner-executor separation, and when each applies.\nOrchestration: building and operating orchestrator agents that decompose tasks, route work to specialist agents or tools, and manage state across multi-step workflows (LangGraph, Strands Agents, CrewAI, or equivalent).\nMemory: short-term/working memory (context management, conversation state) and long-term memory (episodic and semantic stores, vector- and graph-backed retrieval), and the production trade-offs of each.\nReflection and self-correction: critique loops, self-evaluation, retry-with-feedback patterns, and evaluation harnesses that catch agent failures before customers do.\nTool use and function calling: schema design, tool-selection reliability, error handling, and agent-to-agent composition.\nRAG and retrieval pipelines: chunking, embedding, hybrid retrieval, reranking, and grounding agent decisions in customer data.\nStrong AWS production experience: Amazon Bedrock and AWS AI services, plus core platform services (Lambda, API Gateway, DynamoDB, RDS/Aurora, Glue, EMR, Redshift, Kinesis, or similar depending on specialization).\nSolid software engineering fundamentals Python, TypeScript, CI/CD, infrastructure-as-code, testing-driven development discipline.\nExperience with data or application modernization (database migration, legacy refactoring, data platform builds) is a strong plus, since agents run against these workloads.\nIndicative experience: roughly 3-10 years in engineering roles, with agentic AI / GenAI as your current day job. We have demonstrated agent-native expertise over tenure - an engineer with 3-4 years of hands-on agentic AI work typically outperforms a 12-year generalist on this work.\n\nYou'll be preferred if you've:\nUS English verbal and written fluency \nDelivery experience in one or more of our verticals: Financial Services, Healthcare & Life Sciences, Internet & Software, Manufacturing, or Telco/Media/Entertainment/Gaming/Sports.\nModel tuning and fine-tuning: systematic prompt engineering and optimization; parameter-efficient fine-tuning (LoRA/QLoRA or similar); instruction tuning; working knowledge of RLHF/DPO; sound judgment on when to fine-tune vs. prompt vs. RAG; and evaluation of tuned models against baselines. Fine-tuning experience on Amazon Bedrock or SageMaker is a plus.\nExperience with compliance-sensitive AI systems (HIPAA, PCI-DSS, SOC 2, data residency).\nKnowledge graph, code-analysis (AST), or CDC/streaming experience (Debezium, Kafka/MSK).\nSolid software engineering fundamentals - Java, C++, Go Lang, .Net, Rust\nPrior customer-facing consulting or forward-deployed experience.\nAWS certifications (Solutions Architect Professional, Machine Learning Specialty, or Data Analytics).\nWhy This Role?\nYou own outcomes, not tickets. FDEs carry the delivery commitment personally - architecture, judgment, and cutover are yours.\nYou work agent-native from day one. Our delivery model would not function without agents. You build with the platform, not around it.\nYou ship. Engagements measured in weeks to production, legacy retired, outcomes named. No archived pilots.\n You compound. Field delivery informs the Aedeon platform roadmap; the platform's growth expands what you can deliver. Few engineering roles sit in that loop.","description_format":"text","description_chars":5933,"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":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Cloud Consulting & Migration","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2024-10-24T07:33:09Z"}],"visa":[],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":1,"p_active":0.135,"p_room":0.28,"age_days":721,"expected_fill_days":87,"reasons":["conf:3","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-10-16T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/mactores-generative-ai-forward-deployed-engineer","json_url":"https://alion.io/job/mactores-generative-ai-forward-deployed-engineer.json","meta":{"generated_at":"2026-10-16T13:01:28Z","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":12387,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-17T00:00:00Z"}},"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":6938},"rest":"https://alion.io/mcp/rest/get_company?id=6938"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmactores-generative-ai-forward-deployed-engineer"},{"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%2Fmactores-generative-ai-forward-deployed-engineer"},{"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%2Fmactores-generative-ai-forward-deployed-engineer"},{"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/mactores-generative-ai-forward-deployed-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmactores-generative-ai-forward-deployed-engineer"}]}