Assistant Vice President _Applied AI Engineer

Net Connect; Bengaluru; On-site; INR 6,000,000 - 12,000,000; Full time

Job summary

Net Connect is seeking an Assistant Vice President Applied AI Engineer to design and build enterprise-scale AI/ML solutions. The role focuses on Generative AI, Agentic AI, LLM applications, AI evaluation, MLOps, and scalable AI infrastructure.

The successful candidate bridges AI architecture with hands-on engineering, delivering secure and production-ready solutions while mentoring engineers. The role will drive production-grade AI workflows, multi-agent orchestration, and robust APIs.

Qualifications

• 8+ years of software engineering experience, with at least 3+ years building AI/ML systems or scalable ML infrastructure.
• Strong proficiency in Python, particularly FastAPI and asyncio; Go or Java is a plus.
• Production experience developing APIs and microservices across distributed systems.
• Hands‑on experience with Agentic AI and LLM applications, including multi-agent orchestration, tool use, planning frameworks, and multi-step AI workflows.
• Knowledge of prompt engineering and RAG architectures; experience with AI evaluation frameworks is a plus.

Responsibilities

• Design, develop, and deliver production-grade AI/ML solutions and platforms.
• Build agentic AI systems and LLM applications, including multi-agent workflows and tool integrations.
• Develop and optimize multi-step AI workflows and agent orchestration.
• Build AI evaluation frameworks and MLOps tooling for production environments.
• Design scalable APIs and microservices for high-throughput, low-latency workloads.
• Mentor junior engineers and promote engineering best practices.

Skills

AI/ML system design

Python

FastAPI

Asyncio

Go/Java

APIs & microservices

Distributed systems

Agentic AI

LLM applications

MLOps

Prompt engineering

RAG architectures

Multi-agent orchestration

Tool use

Planning frameworks

Security & governance

Mentoring

Stakeholder management

System design

Education

Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related technical discipline

Tools

Docker

Kubernetes

AWS (EC2/EKS, S3, IAM, RDS)

vLLM / OpenAI-compatible APIs

SageMaker / Bedrock

REST / gRPC / OpenAPI

Terraform / CloudFormation

OpenTelemetry

Job description

Role Overview : Assistant Vice President Applied AI Engineer to design and build enterprise-scale AI/ML solutions. The role focuses on Generative AI, Agentic AI, LLM applications, AI evaluation, MLOps, and scalable AI infrastructure. The successful candidate will bridge AI architecture and hands‑on engineering, delivering secure and production-ready solutions while mentoring engineers.

Key Responsibilities

• Design, develop, and deliver production-grade AI/ML solutions and platforms.
• Build agentic AI systems and LLM applications, including multi-agent workflows and tool integrations.
• Develop and optimise multi-step AI workflows and agent orchestration.
• Build AI evaluation frameworks and MLOps tooling for production environments.
• Design scalable APIs and microservices for high-throughput, low-latency workloads.
• Work with product managers, architects, engineers, and business stakeholders to translate requirements into technical solutions.

Participate in code reviews and promote engineering best practices.

• Implement secure coding, testing, monitoring, and governance practices.
• Mentor junior engineers and provide technical guidance.
• Drive AI solutions from system design through implementation and production deployment.

Technical Requirements

• 8+ years of software engineering experience, including at least 3+ years building AI/ML systems, scalable ML infrastructure, or model-serving platforms.

scalable ML infrastructure, or model-serving platforms.

• Strong proficiency in Python, particularly FastAPI and asyncio; experience with Go or Java is also valuable.

valuable.

• Production experience developing APIs and microservices.
• Hands‑on experience developing Agentic AI and LLM applications, including:
• Multi-agent orchestration
• Tool use
• Planning frameworks
• Multi-step AI workflows
• Strong understanding of prompt engineering and RAG architectures.
• Experience with agentic frameworks such as:
• Strands
• LangGraph
• Google ADK
• Experience with LLM model serving, including vLLM and OpenAI-compatible APIs.
• Strong understanding of distributed systems, including:
• Microservices
• REST
• gRPC
• OpenAPI
• Event-driven architectures
• Strong AWS experience, including EC2/EKS, S3, IAM, RDS, and at least one AI service such as Bedrock

or SageMaker.

• Hands‑on experience with Docker and Kubernetes.
• Experience with CI/CD and Infrastructure as Code, particularly CloudFormation or Terraform.
• Knowledge of observability tools such as OpenTelemetry and distributed tracing.

Preferred / Additional Skills

• Experience building AI evaluation frameworks, including agent benchmarking, reasoning traces, and production monitoring.

production monitoring.

• Experience with:
• Vector databases
• Knowledge graphs
• Semantic search
• AI memory systems
• Retrieval optimisation
• Experience implementing AI safety controls such as:
• Guardrails
• Content filtering
• Prompt injection detection
• PII redaction
• Knowledge of NIST AI RMF, MITRE ATLAS, and OWASP LLM Top 10.
• Familiarity with model fine-tuning techniques such as LoRA, RLHF, and supervised fine-tuning.
• Understanding of Responsible AI, model governance, and autonomous AI security.
• Knowledge of Zero Trust, Entra ID, OAuth2, and OIDC.
• Experience with GPU workload management and inference optimisation, particularly vLLM.
• Financial services or banking experience is advantageous.

Leadership & Stakeholder Skills

• Strong system-design and technical problem-solving capabilities.
• Ability to work independently with limited supervision.
• Strong communication and stakeholder management skills.
• Ability to collaborate with technical and non-technical stakeholders.
• Experience mentoring and guiding junior engineers.
• Ability to manage technical risks and contribute to governance and control frameworks.
• Strong understanding of enterprise technology and AI strategy.

Education

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related technical discipline

discipline