Lead AI Engineer

Simpplr is the AI-powered platform that unifies the digital workplace – bringing together engagement, enablement, and services to transform the employee experience. It streamlines communication, simplifies interactions, automates workflows, and elevates the everyday experience of work. The platform is intuitive, highly extensible, and built to integrate seamlessly with your existing technology.

More than 1,000 leading organizations – including AAA, the NHS, Penske, and Moderna – trust Simpplr to foster a more aligned and productive workforce. Headquartered in Silicon Valley with global offices, Simpplr is backed by Norwest Ventures, Sapphire Ventures, Salesforce Ventures, and Tola Capital. Learn more at 

JOB DESCRIPTION

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.

You will lead architecture, development and operationalization of core AI capabilities including MCP, RAG, multimodal processing, LLMs, SLMs and fine-tuned custom ML models with traceability, explainability, auditing and observability built in by design. Your work will blend hands-on engineering with strategic leadership, fostering a culture of Responsible AI while enabling agentic workflows that deliver measurable business impact.

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

A builder-leader who can design enterprise grade systems, ship production code and mentor a high-performance team. Hands-on with AI-native platform design, not just consuming AI APIs but building the foundational components. Relentlessly focused on Responsible AI and the operational realities of running agentic AI in enterprise environments. Excited by the challenge of creating the backbone of Simpplr's Agentic universe from scratch.

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At Simpplr we believe that when work is good, life is better and that belief guides all we do. Including how we approach our flexible work model. Simpplr operates with a Hub-Hybrid-Remote model. This model is role-based with exceptions and provides employees with the flexibility that many have told us they want.

• Hub - 100% work from Simpplr office. Role requires Simpplifier to be in the office full-time.
• Hybrid - Hybrid work from home and office. Role dictates the ability to work from home, plus benefit from in-person collaboration on a regular basis. 
• Remote - 100% remote. Role can be done anywhere within your country of hire, as long as the requirements of the role are met.