---
title: 'Generative AI Forward Deployed Engineer at Mactores'
canonical: 'https://feeny.ai/job/generative-ai-forward-deployed-engineer-mactores-mumbai-7xde4h79h517'
type: 'job'
last_seen: '2026-10-16'
---

# Generative AI Forward Deployed Engineer at Mactores

- **Company:** Mactores
- **Location:** Mumbai, India
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2024-10-24
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.lever.co/mactores/07c51b46-27fc-4400-a5ac-69bb0d335ce0

## Job description

Mactores is the agent-native AWS modernization firm. Most modernization work doesn't ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores' founders' sister company, which absorbs the repetitive 60–70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.

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. The 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. This is not a staff-augmentation seat and not an advisory role. You ship.

What you will do?

- Deliver 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.
- Build and productionize AI agents, orchestration, retrieval pipelines, evaluation harnesses, observability running against real customer data, not demo data.
- Convert 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.
- Convert 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.
- Embed directly with customer engineering teams. Run architecture sessions, defend design decisions, and align stakeholders from VP Engineering to CTO.
- Make 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).
- Feed field experience back into the platform and practice: your deployment patterns, integration playbooks, and edge cases shape how we deliver.

What are we looking for?

- 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.
- You 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.
- Deep understanding of agentic architecture — you can design an agent system from first principles and explain why each component exists:

-

- Agent design patterns: single-agent vs. multi-agent systems, supervisor/orchestrator patterns, hierarchical agent topologies, planner–executor separation, and when each applies.
- Orchestration: 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).
- Memory: 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.
- Reflection and self-correction: critique loops, self-evaluation, retry-with-feedback patterns, and evaluation harnesses that catch agent failures before customers do.
- Tool use and function calling: schema design, tool-selection reliability, error handling, and agent-to-agent composition.
- RAG and retrieval pipelines: chunking, embedding, hybrid retrieval, reranking, and grounding agent decisions in customer data.
- Strong 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).
- Solid software engineering fundamentals Python, TypeScript, CI/CD, infrastructure-as-code, testing-driven development discipline.
- Experience with data or application modernization (database migration, legacy refactoring, data platform builds) is a strong plus, since agents run against these workloads.
- Indicative 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.

You'll be preferred if you've:

- US English verbal and written fluency
- Delivery experience in one or more of our verticals: Financial Services, Healthcare & Life Sciences, Internet & Software, Manufacturing, or Telco/Media/Entertainment/Gaming/Sports.
- Model 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.
- Experience with compliance-sensitive AI systems (HIPAA, PCI-DSS, SOC 2, data residency).
- Knowledge graph, code-analysis (AST), or CDC/streaming experience (Debezium, Kafka/MSK).
- Solid software engineering fundamentals — Java, C++, Go Lang, .Net, Rust
- Prior customer-facing consulting or forward-deployed experience.
- AWS certifications (Solutions Architect Professional, Machine Learning Specialty, or Data Analytics).

Why This Role?

- You own outcomes, not tickets. FDEs carry the delivery commitment personally — architecture, judgment, and cutover are yours.
- You work agent-native from day one. Our delivery model would not function without agents. You build with the platform, not around it.
- You ship. Engagements measured in weeks to production, legacy retired, outcomes named. No archived pilots.
- 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.

Life at Mactores

We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.

1. Be one step ahead
2. Deliver the best
3. Be bold
4. Pay attention to the detail
5. Enjoy the challenge
6. Be curious and take action
7. Take leadership
8. Own it
9. Deliver value
10. Be collaborative

We would like you to read more details about the work culture on https://mactores.com/careers

The Path to Joining the Mactores Team At Mactores, our recruitment process is structured around three distinct stages:

Pre-Employment Assessment: A series of evaluations of your technical proficiency and suitability for the role.

Managerial Interview: The hiring manager engages with you in multiple discussions, 30 minutes to an hour each, covering technical skills, hands-on experience, leadership potential, and communication.

HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team.

Mactores provides equal opportunities in all employment practices. We don't discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This applies to every part of the employment relationship, recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs.

Note: Please answer as many questions as possible with this application to accelerate the hiring process.

## About Mactores

## Company Overview
- **One-liner**: Mactores is an agent-native AWS modernization firm that delivers data platform, application, and AI agent projects for enterprise customers using a proprietary agent platform (Aedeon) and forward-deployed engineers.
- **Entity Type**: Private (Privately Held, no disclosed funding rounds)
- **Headquarters**: Bellevue, Washington, United States
- **Founded**: 2008
- **Founders**: Bal Heroor (CEO) and Nandan Umarji (COO)

## Core Business
- **Primary industry**: Cloud consulting & modernization / IT services (specializing in AWS, data platforms, and AI agents)
- **Target customers**: Fortune 500 companies, high-growth software teams (B2B enterprise)
- **Mission or purpose**: “Build the firm that builds the AI era.” Deliver modernizations that “compound for years, finished in weeks instead of quarters.”

## Products & Services
- **Aedeon Agent Platform**: Proprietary internal platform that absorbs 60–70% of engagement work (discovery, mapping, validation, cutover instrumentation), replacing the traditional consulting pyramid.
- **Data Platform Modernization**: Modernize data foundations to enable AI readiness, completed in weeks rather than quarters.
- **Application & Database Modernization**: Migrate and refactor legacy apps and databases to AWS-native architectures.
- **AI Agents for Apps**: Deploy production-grade AI agents for real operations (customer support, claims processing, real-time decision grids).

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metrics**:
  - Annual Revenue: $5M (per LinkedIn, though company website states “200+ AWS-certified engineers” suggesting a larger scale)
  - Headcount: Conflicting reports – LinkedIn lists 65 employees (with +5.4% YoY growth), while the company website claims “200+ AWS-certified engineers.” Actual headcount likely higher than 65.
  - 7 AWS Consulting Competencies, 17 AWS Service Validations, Agentic AI Specialization, AWS Premier Tier Services Partner.
- **Notable Investors/Partners**: No external investors disclosed. Key partners include AWS (Premier Tier Partner) and customers such as Safaricom, Synaptics, Flipboard, Poshmark, Seagate, HP, Adani, DocuSign, KlearTrust, Tilia, Sterne Kessler, and Total Expert.
- **Growth Signals**: Headcount growth of +5.4% YoY (per LinkedIn), active job postings (+33.3% month-over-month), and expansion into AI agent delivery with Aedeon platform.

## Competitive Advantages
- **Agent-native delivery model**: Aedeon replaces the junior-heavy pyramid by automating 60–70% of engagement hours, allowing a lean team of senior forward-deployed engineers to own architecture and cutover directly.
- **Fixed-date, fixed-fee contracts**: Engagements close on customer-signed acceptance, not status reviews, reducing risk for clients.
- **Deep AWS credentials**: One of the first specialist AWS adoption practices, with Premier Tier Partner status, 7 competencies, and 200+ AWS-certified engineers – a credential set that procurement teams trust.

## Strategic Focus
- Scale the agent-native model across more enterprise engagements.
- Deepen specialization in Generative AI and Agentic AI on AWS.
- Continue to invest in Aedeon, the internal agent platform, to further reduce delivery hours and enable faster modernization cycles.
- Expand headcount with senior engineers who can operate as delivery owners.

## Why Work Here
- **Culture**: Pragmatic, principle-driven environment (“Ten Core Leadership Principles”). Everyone is expected to get in the trenches; top-down teamwork and ownership are emphasized.
- **Work/Life Balance**: Scrum-based planning with day, week, sprint, and quarterly goals. Proactive communication prevents last-minute confusion. Time off is encouraged.
- **Learning & Development**: 20% of every Mactorian’s time is dedicated to learning new technologies. AWS certifications are fully funded and treated as staffing-quality investments.
- **Role Clarity**: Engineers are not placed on a pyramid under a thin senior layer. Every Mactores forward-deployed engineer is a senior delivery owner who personally signs off on production cutovers.
- **Remote/Hybrid**: Mixed – some roles are fully remote (e.g., Channel Partner Manager, Technical Content Writer), while others (e.g., Business Development Representative in Mumbai) are hybrid. Open roles listed on Lever.
- **Notable Perks**: Permanent learning time, career progression tied to principles and delivery outcomes.

## Sources
1. [mactores.com/about](https://mactores.com/about)
2. [mactores.com/careers](https://mactores.com/careers)
3. [jobs.lever.co/mactores](https://jobs.lever.co/mactores)
4. [linkedin.com/company/mactores](https://linkedin.com/company/mactores)
5. [mactores.com](https://www.mactores.com/?hsLang=en)

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