Manager - AI Forward Deployed Engineering

Vibehackers; Bengaluru; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Vibehackers seeks a Manager — AI Forward Deployed Engineer to lead end-to-end design, build, and deployment of production-grade GenAI solutions for clients. You will craft LLM-driven apps, RAG systems, and agentic workflows while delivering measurable business value and reusable accelerators.

Qualifications include 9+ years in software, data, or AI/ML, expert Python, distributed systems, APIs, and cloud-native architectures; strong client-facing delivery and excellent communication with

Qualifications

• 9+ years in software, data, or AI/ML engineering.
• Proven ability to deliver production-grade systems.
• Expert Python for large-scale apps.
• Strong distributed systems, APIs, and cloud-native knowledge.
• Client-facing delivery in high-ambiguity environments.
• Excellent communication with clients and stakeholders.
• Ability to own and deliver complex initiatives independently.

Responsibilities

• Lead end-to-end delivery at strategic customers from discovery to production deployment.
• Translate business problems into GenAI solutions with client teams.
• Build LLM-powered apps, RAG systems, and agentic workflows.
• Optimize latency, cost, accuracy, security, and compliance.
• Create reusable accelerators and reference architectures.
• Architect scalable, observable cloud-native systems.
• Provide trusted technical guidance to senior client stakeholders.

Skills

Python

Distributed systems

Microservices

APIs

Cloud-native architectures

Client-facing delivery

Communication

Hands-on coding

DevOps

Tools

OpenAI

Claude

Cursor

Palantir

Azure

AWS

GCP

Job description

Manager - AI Forward Deployed Engineering

Uses Cursor and LLM APIs to build GenAI apps and agentic workflows—directly tied to vibe coding with AI assistants and rapid prototyping.

About the Role

Lead end-to-end design, build, and deployment of production-grade GenAI solutions as a hands-on Forward Deployed Engineer working directly with clients. Build LLM-driven applications, RAG systems, and agentic workflows while creating reusable accelerators and enabling large-scale AI adoption.

Job Description

Role

Manager — Forward Deployed Engineer (AI & Data). Responsible for designing, building, and deploying production-grade GenAI and AI/ML solutions directly with clients. Focus on building LLM-driven applications, RAG systems, and agentic workflows and delivering measurable business value while creating reusable accelerators and reference architectures.

Key Responsibilities

• Lead end-to-end delivery at strategic customers: discovery, design, development, and production deployment.
• Translate complex business problems into executable GenAI solutions in partnership with client business and engineering teams.
• Build LLM-powered applications (copilots, assistants), RAG systems, and agentic workflows; integrate with enterprise data platforms, APIs, and external systems.
• Optimize solutions for latency, cost, accuracy, scalability, security, and compliance.
• Convert proofs-of-concept into production-grade, enterprise-ready platforms through rapid iteration.
• Architect scalable, reliable, and observable systems using cloud-native patterns.
• Create reusable accelerators, reference implementations, and best practices for enterprise GenAI adoption.
• Act as a trusted technical advisor to senior and executive client stakeholders.

Requirements

Mandatory

• 9+ years of experience in software engineering, data engineering, or AI/ML.
• Strong hands‑on experience building, deploying, and operating production-grade systems.
• Expert‑level proficiency in Python for large‑scale, high‑performance applications.
• Solid foundation in distributed systems, microservices, APIs, and cloud-native architectures.
• Proven delivery experience in client‑facing and high‑ambiguity environments.
• Excellent communication skills with technical teams and business stakeholders; client experience required.
• Demonstrated ability to independently own and deliver complex, high‑impact initiatives.

Desired / Preferred

• Hands‑on experience with LLM APIs, prompt engineering, RAG architectures, and vector databases.
• Experience with agentic workflows and orchestration frameworks.
• Exposure to AI ecosystem tools such as OpenAI, Claude, Cursor, Palantir, and hyperscalers (Azure, AWS, GCP).
• Experience with DevOps, CI/CD pipelines, infrastructure automation, MLOps practices, and model monitoring.
• Consulting, global delivery, or field engineering experience with direct client exposure; prior FDE/solutions/field engineer background.
• Experience building 0→1 AI or data products; frontend/UI exposure for AI‑driven applications.

What This Role Is Not

• Not a people management role.
• Not a delivery governance or program management role.
• Not limited to architecture reviews — expected to build and ship.

Attributes

• Deep technical expertise and a builder mindset; senior engineer who codes regularly.
• Comfortable in ambiguous, client‑facing environments and able to learn quickly.

Python LLM APIs RAG (Retrieval-Augmented Generation) Agentic workflows Vector databases OpenAI Claude Cursor Palantir Azure AWS GCP CI/CD DevOps Cloud-native patterns APIs MLOps Prompt engineering

Skills

System Design Distributed Systems Microservices APIs Cloud-native Architecture Communication Client‑facing Delivery Solution Delivery Rapid Prototyping Hands‑on Coding DevOps CI/CD Infrastructure Automation MLOps Prompt Engineering Technical Leadership Integration Scalability & Reliability Model Monitoring

Python LLM APIs RAG (Retrieval-Augmented Generation) Agentic workflows Vector databases OpenAI Claude Cursor Palantir Azure AWS GCP CI/CD DevOps Cloud-native patterns APIs MLOps Prompt engineering