Senior AI engineer

Porce Consulting Services LLC; Chennai District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Porce Consulting Services LLC is seeking a Senior AI Engineer to design, build, and operate end-to-end AI and GenAI solutions in production. You will own data pipelines, APIs, deployments, and monitoring across the full lifecycle while collaborating with business and engineering teams.

You will lead implementation of LLM-based systems, optimize models, and contribute to governance, security, and CI/CD practices inside a dynamic enterprise environment.

Qualifications

• 7+ years of software/data/AI engineering experience.
• 3+ years building AI/GenAI systems in production.
• Experience taking AI systems from concept to production.

Responsibilities

• Design and build end-to-end AI/ML/GenAI solutions from scratch.
• Translate business problems into scalable AI system designs.
• Develop production-ready AI applications, including APIs, backend services, workflows, and user-facing AI features.
• Build and maintain data pipelines for training, inference, evaluation, and monitoring.
• Implement LLM-based solutions using RAG, prompt engineering, embeddings and vector databases.
• Evaluate and optimize models for accuracy, latency, and cost.
• Deploy AI workloads on cloud or containers using CI/CD, Docker, Kubernetes, and MLOps.
• Monitor production AI systems for drift and risks and collaborate with cross-functional teams.
• Create documentation, architecture diagrams, and runbooks.
• Mentor junior engineers and promote best practices in AI engineering.

Skills

Python programming

FastAPI/Flask

PyTorch/TensorFlow

LLMs & RAG

Prompt engineering

Embeddings & vector search

Docker & Kubernetes

CI/CD

Cloud platforms (AWS/Azure/GCP)

APIs & microservices

Data pipelines

Education

Bachelor’s or Master’s degree in CS/DS/AI

Tools

LangChain

LlamaIndex

MLflow

OpenAI/Azure OpenAI

Hugging Face

Job description

We are looking for a Senior AI Engineer with strong hands-on experience in designing,

building, deploying, and operating AI systems in production. The ideal candidate should

have built AI/ML or GenAI solutions from the ground up, including architecture, model

development, data pipelines, APIs, deployment, monitoring, and continuous improvement.

This role requires someone who can work across the full AI lifecycle — from problem

discovery and solution design to production-grade implementation — while collaborating

closely with business users, data teams, engineering teams, and platform stakeholders.

Key Responsibilities

• Design and build end-to-end AI, Machine Learning, and Generative AI solutions from scratch.
• Translate business problems into scalable AI system designs and technical implementation plans.
• Develop and deploy production-ready AI applications, including APIs, backend services, workflows, and user-facing AI features.
• Build and maintain data pipelines required for model training, inference, evaluation, and monitoring.
• Implement LLM-based solutions using RAG, prompt engineering, agentic workflows, embeddings, vector databases, and orchestration frameworks.
• Evaluate, fine-tune, and optimize models for accuracy, latency, cost, reliability, and business impact.
• Design secure and governed AI systems with proper access control, data privacy, auditability, and responsible AI practices.
• Deploy AI workloads on cloud or containerized platforms using CI/CD, Docker, Kubernetes, and MLOps/LLMOps practices.
• Monitor production AI systems for performance drift, hallucination risks, failures, cost anomalies, and user adoption.
• Collaborate with product owners, data engineers, software engineers, architects, and business teams to deliver measurable outcomes.
• Create technical documentation, architecture diagrams, deployment guides, and operational runbooks.
• Mentor junior engineers and support best practices in AI engineering, code quality, testing, and production operations.

Required Skills & Experience

• 7+ years of overall experience in software engineering, data engineering, AI engineering, or machine learning engineering.
• 3+ years of hands-on experience building AI/ML or GenAI systems for real-world business use cases.
• Proven experience taking AI systems from concept to production.
• Strong programming skills in Python, with experience in frameworks such as FastAPI, Flask, PyTorch, TensorFlow, scikit-learn, or similar.
• Experience with LLMs, RAG architectures, prompt engineering, embeddings, vector search, and AI orchestration frameworks.
• Hands-on experience with tools such as LangChain, LlamaIndex, MLflow, OpenAI/Azure OpenAI, Anthropic, Hugging Face, or equivalent platforms.
• Strong understanding of data pipelines, feature engineering, model evaluation, inference pipelines, and model monitoring.
• Experience deploying applications using Docker, Kubernetes, CI/CD pipelines, and
• Good knowledge of cloud platforms such as AWS, Azure, or GCP.
• Strong understanding of APIs, microservices, event-driven architecture, and
• Experience with databases, data lakes, warehouses, and vector databases.
• Ability to write clean, modular, testable, and maintainable code.
• Strong problem-solving skills and ability to work with ambiguous business requirements.

Preferred Skills

• Experience with enterprise AI platforms, LLMOps, MLOps, or data platforms such as
• Experience building AI agents, workflow automation, decision-support systems, or
• Knowledge of model governance, responsible AI, data privacy, security, and compliance requirements.
• Experience with real-time or near-real-time AI inference systems.
• Exposure to operational domains such as aviation, logistics, supply chain, workforce planning, customer operations, or enterprise analytics.
• Experience optimizing GenAI solutions for cost, latency, accuracy, and reliability.
• Familiarity with observability tools, logging, tracing, model monitoring, and production support processes.

Educationss

• Bachelor’s or master’s degree in computer science, Data Science, Artificial