Artificial Intelligence Engineer

InCommon

Pune City

On-site

INR 800,000 - 1,200,000

Full time

14 days+

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Benefits offered by this job

Fast-paced environment

Learning and experimentation opportunities

Collaboration with talented teams

Job summary

A global technology consultancy in Pune is seeking an AI Engineer to build and optimize AI solutions, focusing on LLM systems for real-world applications. The role involves full development lifecycle from data pipelines to production integration, emphasizing performance and business value. Ideal candidates will have strong programming skills, experience with AI/ML tools, and a proactive approach to problem-solving.

Qualifications

3–7 years of hands-on experience in AI/ML engineering.
Proven ability to design, fine-tune, and deploy LLMs.
Strong programming expertise in Python with production experience.

Responsibilities

Fine-tune, deploy, and evaluate LLMs tailored to client-specific use cases.
Design and build high-performance data ingestion and processing pipelines.
Develop monitoring dashboards and alerting systems for AI model performance.

Skills

Python

AI/ML Engineering

Communication

Tools

scikit-learn

PyTorch

TensorFlow

Hugging Face

MLflow

Kubeflow

AWS

GCP

Azure

Job description

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InCommon is hiring on behalf of a Global Technology Solutions provider based in Pune.

About Us

We are a global technology consultancy focused on building ambitious digital products. Our team of engineers, designers, and product managers approach their work as a craft — obsessing over quality, innovation, and real-world impact.

About the Role

We are looking for an AI Engineer to build, deploy, and optimize AI solutions — especially Large Language Model (LLM) systems — for real-world business applications. You'll work across the full development lifecycle: from setting up data pipelines to integrating AI into production environments, with a strong focus on performance, monitoring, and business value.

You’ll thrive in this role if you enjoy working independently, navigating ambiguity, and pushing AI systems from experimentation to scalable, production-grade solutions.

Key Responsibilities

Fine-tune, deploy, and evaluate LLMs tailored to client-specific use cases.
Implement retrieval-augmented generation (RAG) systems and vector database integrations.
Design and build high-performance data ingestion, transformation, and processing pipelines for training and inference workflows.
Architect end-to-end AI systems, selecting the right tools, cloud services, and ML frameworks to meet business and technical goals.
Integrate observability and testing into pipelines to ensure continuous validation and model health.

Orchestration & Automation

Build multi-agent AI workflows using tools like n8n, relay.app, and a variety of plugins (e.g., Byword, Exa, Clay).
Automate processes for deployment, testing, and updates across different stages of development.

Monitoring & Observability

Develop monitoring dashboards and alerting systems to track AI model performance, data drift, and inference quality.
Establish evaluation pipelines to assess impact across changing variables and ensure robustness.
Partner with design, product, and engineering teams to translate business goals into technical implementations.
Mentor and support junior engineers, sharing best practices in AI/ML system design.
Stay up-to-date with advancements in AI/ML, LLMs, and MLOps.
Contribute internally through case studies, blogs, and workshops to foster a culture of knowledge sharing.

What We're Looking For

3–7 years of hands-on experience in AI/ML engineering.
Strong programming expertise in Python, with production experience using libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face, etc.
Proven ability to design, fine-tune, and deploy LLMs and multi-agent systems in real-world environments.
Hands-on experience with vector databases, prompt engineering, and RAG architectures.
Familiarity with AI/MLOps workflows and tools like MLflow, Kubeflow, or similar.
Exposure to multimodal AI systems involving text, image, or audio inputs.
Proficient in building cloud-native applications with AWS, GCP, or Azure.
Strong communicator who is proactive in surfacing blockers, brainstorming solutions, and collaborating cross-functionally.

Nice to Have

Experience working in startups or consultancy environments.
Exposure to serverless architectures and scalable AI infrastructure.
Awareness of AI ethics, privacy, and compliance frameworks.

Why Join Us?

Build real, production-grade AI systems — not just prototypes.
Collaborate with talented engineers, designers, and product leads who care deeply about building with purpose and precision.
Work directly with customers in their 0-1 and 1-n journeys, helping shape solutions from scratch.
A fast-paced environment that encourages learning, experimentation, and continuous feedback.

Seniority level