Lead AI Engineer

LEAD AI ENGINEER

About the Role

As Principal/Lead AI Engineer at Simpplr, you will spearhead the transformation of our platform from AI-enabled to AI-native, architecting and delivering Simpplr s native AI platform from the ground up. This platform will power Simpplr s Agentic universe, driving next-gen agentic workflow automation along with personalization and recommendations at enterprise scale.

MCP, RAG, multimodal processing, LLMs, SLMs

Key Responsibilities

• Design, code and lead the build of Simpplr s AI-native platform embedding explainability, traceability, observability and auditing as core capabilities


• Deliver enterprise-scale AI capabilities using MCP, RAG, multimodal, LLMs, SLMs, fine-tuned custom ML models and agentic workflow automation.


• Define technical strategy and roadmap; align with product and engineering leaders to deliver customer value at speed and scale.


• Establish and champion Responsible AI principles like bias detection, privacy-by-design, compliance with security and governance standards.


• Build robust AIOps and MLOps pipelines with versioning, CI/CD, monitoring, rollback and drift detection.


• Mentor engineers and data scientists to build high-trust and high-performance AI teams.


• Partner with cross-functional teams to integrate AI into core product experiences and ensure measurable impact on user engagement and productivity.
  
  
  
  

What We Are Looking For

• 8+ years in applied AI/ML engineering with proven leadership in building complex, high-scale AI platforms or products.


• Experience in designing and delivering advanced AI solutions using LLMs/SLMs, MCP architecture, RAG pipelines, Vector DBs, Agentic AI workflows and automations.


• Experience in building AI solutions with native observability, explainability and compliance features.


• Strong background in AIOps/MLOps, data engineering and large-scale inference optimization.


• Track record of translating product goals into technical execution with measurable business outcomes.


• Ability to build and nurture high performing AI teams and foster a culture of innovation, accountability and trust


• Curiosity and eagerness to learn about next generations of agentic AI workflows, personalization and LLM-based solutions.
  
  
  
  

Technical Skill Sets

• AI/ML:

  LLMs, MCP (Model Context Protocol), RAG, multimodal generation, SLMs, prompt engineering.



• Programming:

  Python, PyTorch/TensorFlow, scikit-learn, full-stack engineering experience is a plus.



• Data Engineering:

  SQL/NoSQL, Snowflake, BigQuery, Databricks, Vector databases such as FAISS, Milvus, Pinecone, Redis.



• MLOps & AIOps:

  CI/CD, model versioning, monitoring, observability, anomaly detection, Docker, Kubernetes, Kafka, Spark, Triton, TorchServe, MLFlow.



• Cloud Infrastructure:

  AWS, GCP, Azure; Terraform, Ansible for secure and scalable deployments.



• Responsible AI & Governance:

  Bias detection, interpretability, audit trails, privacy-by-design and compliance frameworks.

Our Ideal Candidate

Responsible AI

.