Senior AI Engineer - Career

Vibehackers; Pune District; On-site; INR 2,500,000 - 4,200,000; Full time

Benefits offered by this job

Hybrid work setup in Pune

Healthcare package

Online learning platform with guided

Job summary

Vibehackers is seeking a Senior AI Engineer to lead architecture and delivery of cloud-native AI agent systems on Google Cloud Platform, leveraging LangChain/LangGraph and AI code-assist tools to accelerate development and prototyping.

You will mentor a cross-functional team, drive technical strategy, and ensure scalable APIs and microservices with robust observability and DevSecOps practices.

Qualifications

• Bachelor’s degree or equivalent experience in a related field.
• 5+ years in software engineering shipping complex, scalable systems.
• 1+ years in an AI/ML role with hands-on model integration and MLOps.
• 1+ years building with LangChain/LangGraph or similar frameworks.
• 2+ years with GCP AI/ML services (Vertex AI).
• 3+ years in Kubernetes workloads.
• Hands-on with Langfuse observability tools.
• CI/CD experience (GitHub Actions, Argo CD, Jenkins).
• SQL and NoSQL databases experience.

Responsibilities

• Lead design, build, and deployment of production-scale AI agents on GCP.
• Define engineering strategy, architecture, and roadmaps.
• Mentor cross-functional team across software, reliability, and quality.
• Drive MLOps, observability, and governance practices.
• Develop and refine prompts, context data, and AI workflows.
• Collaborate with product, SRE, and stakeholders; report metrics (SLA/SLO).
• Lead incident resolution, troubleshooting, and technical documentation.

Skills

System Architecture

Cloud Architecture

MLOps

Prompt Engineering

Context Engineering

Observability

Kubernetes

CI/CD

Mentoring

Technical Leadership

Troubleshooting

Documentation

Research & Prototyping

Education

Bachelor’s degree or equivalent experience

Tools

Docker

Kubernetes

Terraform

CloudFormation

GitHub Actions

Argo CD

Jenkins

LangChain

LangGraph

Langfuse

Vertex AI

Job description

Explicitly mentions vibe coding and using AI code-assistants (GitHub Copilot, Gemini, Claude) to accelerate development and prototyping.

About the Role

Lead a team to design, build, and deploy production-scale, cloud-native AI agent systems on Google Cloud Platform, leveraging agentic frameworks like LangChain/LangGraph and AI code-assist tools to accelerate development. Drive architecture, MLOps, observability, and mentoring while partnering with product and engineering stakeholders to deliver scalable APIs and microservices.

Job Description

Role

Senior AI Engineer to lead architecture and delivery of cloud-native AI agent systems and platform services. The role focuses on designing, building, and operating production-scale AI agents and services on Google Cloud Platform, mentoring a cross-functional team, and driving technical strategy and best practices.

Key Responsibilities

• Design, build, and deploy complex AI agents using LangChain and LangGraph.
• Design, test, and refine prompts and contextual data frameworks (prompt & context engineering).
• Identify, prototype, and integrate foundational models, RAG techniques, and agentic frameworks.
• Engineer and operate AI systems at production scale on Google Cloud Platform (GCP), including Vertex AI services.
• Establish MLOps practices for agentic systems (reliability, versioning, monitoring, observability) using tools like Langfuse.
• Use AI-powered coding assistants (e.g., GitHub Copilot, Gemini, Claude) to accelerate development, documentation, testing, and observability.
• Build, manage, and mentor a cross-functional team of software, quality, and reliability engineers.
• Define and report on engineering metrics (SLA, SLO, SLI) and enforce DevSecOps and FinOps best practices.
• Collaborate with product managers, architects, SREs, and business partners to set technical strategy and roadmaps.
• Lead troubleshooting, incident resolution, and participate in agile ceremonies (Sprint Planning, Retrospectives).
• Drive and maintain technical documentation, runbooks, and deliver technical presentations to stakeholders.

Requirements

• Bachelor’s degree or equivalent experience.
• 5+ years in software engineering with experience shipping complex, scalable systems.
• 1+ years in a dedicated AI/ML role with hands-on model integration and MLOps experience.
• 1+ years building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
• 2+ years working with Google Cloud Platform (GCP) AI/ML services (e.g., Vertex AI).
• 3+ years of experience with Kubernetes workloads.
• Hands-on experience with LLM observability tools such as Langfuse.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Infrastructure as Code experience (Terraform or CloudFormation).
• CI/CD experience (GitHub Actions, Argo CD, Jenkins).
• Database experience with SQL (Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB, Firestore).

Preferred / Nice-to-have

• Strong expertise in Generative AI and experience with models like Gemini, ChatGPT, Claude, or Llama.
• Experience creating and deploying AI agents to production environments.
• Demonstrated use of AI code assistants to accelerate development and improve quality.
• Track record of solving ambiguous, complex technical challenges and mentoring teams.

Benefits & Work Model

• Hybrid work setting based in Pune, India.
• Comprehensive compensation and healthcare packages.
• Paid time off and organizational growth opportunities via an online learning platform with guided career tracks.

Skills

System Architecture Cloud Architecture MLOps Prompt Engineering Context Engineering Observability Monitoring Containerization Kubernetes CI/CD Infrastructure as Code DevSecOps FinOps Agile Sprint Planning Mentoring Technical Leadership Troubleshooting Performance Optimization Technical Communication Research & Prototyping Data-driven decision making Documentation

Experience Level

Senior

Employment Type

Full-time

• Hybrid work setting
• Paid time off
• Online learning platform with guided career tracks