Principal AI Engineer

Principal AI Engineer

Let’s be unstoppable together!

At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We have a global commitment to diversity, equity, and inclusion as we believe in the undeniable strength that diversity brings to our business, employees, clients, and communities. With us, you can always bring your full self to work. Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®. This prestigious award is based entirely on what current employees say about their experience working at Circana.

Learn more at www.circana.com.

What will you be doing?

We are seeking Principal AI Engineer, who will own end-to-end technical implementation of the Agentic AI onboarding platform, partnering with the Head of AI New Frontiers to deliver multiagent systems, client onboarding automation, supervised learning, and production grade AI workflows. This role blends hands-on development, technical leadership, and client aligned solutioning.

Job Responsibilities

AI Engineering & AI Workflow Development

• Lead development of multiagent orchestration layers using Python, LangChain, and generative AI models.
• Translate client data onboarding needs into reusable playbooks, workflows, and accelerators.
• Architect integration patterns across Spark pipelines, Context Studio, and downstream data systems.
• Build and maintain supervised learning pipelines that convert analyst corrections into durable knowledge.
• Partner with platform engineers on data ingestion, pipeline automation, and metadata driven workflow execution.
• Review and elevate code quality, design patterns, and engineering standards across the team.
• Serve as the technical SME for client use cases, advising on feasibility, architecture, and solution patterns.
• Mentor junior and senior engineers; drive adoption of best-in-class LLM engineering and prompt/context/memory engineering practices.
• Work closely with product, delivery, and analytics teams to ensure successful onboarding and adoption across engagements. Enforce best practices for data quality, governance, and security throughout the data lifecycle
• Ensure data availability, reliability and performance through monitoring and automation.

Big Data & Analytics

• Build and optimize large-scale data processing pipelines using Apache Spark and PySpark 
• Implement data partitioning, caching, and performance tuning for Spark-based workloads.

• Work with diverse data formats (structured and unstructured) to support advanced analytics and machine learning initiatives.

Team Leadership & Collaboration

• Foster a collaborative environment and promote best practices for coding standards, version control, and documentation.
• Engage directly with clients to understand business needs, communicate technical concepts clearly.
• Collaborate with peers across engineering, product, architects to drive scalable and maintainable product
• Partner with the Program Management team to align delivery timelines, mitigate risks

Requirements

• 8-15 years in software engineering, data engineering, AI engineering, or distributed systems.
• Proven delivery of production systems (not only POCs), ideally involving data pipelines or AI-assisted workflows.
• Comfortable working in a distributed global team with overlapping time zones.
• Hands-on experience with LangChain / LangGraph / LlamaIndex / AutoGen or similar agent frameworks.
• Strong understanding of RAG, tool/function calling, orchestration, and prompt engineering patterns.
• Experience implementing agent memory (vector memory + structured memory) and quality-improvement loops (self-critique/evaluation).
• Familiarity with vector databases and retrieval optimization (indexing strategies, reranking, grounding techniques).
• Experience with graph databases / knowledge graphs (Neo4j, TigerGraph, Neptune, Memgraph, etc.).
• Strong Python engineering skills (APIs, services, performance profiling, async/concurrency a plus).
• Strong Spark experience (ETL/ELT, performance tuning, distributed debugging).
• Strong SQL and data modeling skills; experience working with large-scale datasets.
• Solid software engineering fundamentals: testing, CI/CD, Git workflows, code quality, and observability basics.
• Nice to have experience of LLMOps/ MLOps

Circana Behaviors

As well as the technical skills, experience and attributes that are required for the role, our shared behaviors sit at the core of our organization. Therefore, we always look for people who can continuously champion these behaviors throughout the business within their day-to-day role:

• Stay Curious: Being hungry to learn and grow, always asking the big questions.
• Seek Clarity: Embracing complexity to create clarity and inspire action.
• Own the Outcome: Being accountable for decisions and taking ownership of our choices.
• Center on the Client: Relentlessly adding value for our customers.
• Be a Challenger: Never complacent, always striving for continuous improvement.
• Champion Inclusivity: Fostering trust in relationships engaging with empathy, respect, and integrity.
• Commit to each other: Contributing to making Circana a great place to work for everyone.

Location

This position can be located in the following area(s): India Hub