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
Model Development & Integration
- Fine-tune, deploy, and evaluate LLMs tailored to client-specific use cases.
- Implement retrieval-augmented generation (RAG) systems and vector database integrations.
Data Pipelines
- Design and build high-performance data ingestion, transformation, and processing pipelines for training and inference workflows.
AI/ML System Architecture
- 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.
Collaboration & Mentorship
- 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.
Continuous Learning & Sharing
- 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
- 37 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.
