Engineering Manager — AI Engineering

About Innovapptive

Innovapptive is an enterprise SaaS company building an AI-powered Connected Worker Platform for industrial organizations. Our platform connects frontline workers back-office systems and assets in real-time to drive safety reliability and operational productivity.

Leading global enterprises including Shell Hess Westlake Chemical Kimberly-Clark Scott Miracle-Gro and Newmont Mining rely on Innovapptive to transform how work gets done across plants and field operations.

Our customers have achieved $50M EBITDA savings at a single enterprise 10 improvement in frontline productivity and 1520% reductions in maintenance costs.

Innovapptive is recognized as a Leader in Frost & Sullivans Frost Radar 2025 - Augmented Connected Worker Platforms with acknowledgments from Gartner and LNS Research and is backed by Vista Equity Partners and Tiger Global Management.

With headquarters in Houston and an engineering center in Hyderabad we have 300 employees across the U.S. India and ANZ and are on a strong trajectory toward $100M ARR.

The Role

Innovapptives Connected Worker Platform is expanding its AI capability from foundational features into a broad portfolio of product-facing AI agents purpose-built for industrial field operations. These agents span maintenance planning work order automation safety compliance operator rounds and knowledge assistance all grounded in customer-specific asset data and SOPs.

This role leads the AI Engineering team responsible for designing building and operating that agent portfolio in production. You own the full lifecycle: from architecture and prompt engineering through evaluation deployment and reliability. You work closely with Product Platform and customer-facing teams to translate industrial use cases into AI capabilities that enterprise customers trust.

What You Own

• AI Engineering team across agent development LLM infrastructure and model evaluation.
• End-to-end agent lifecycle: requirements through architecture build evaluation deployment and production monitoring.
• RAG and knowledge infrastructure: document ingestion pipelines chunking strategies embedding vector search and knowledge graph grounding.
• LLM governance: model selection prompt versioning bias testing audit logs and human-in-the-loop controls. All inference within Innovapptives AWS VPC no data to external LLM endpoints.
• Agent quality: evaluation frameworks accuracy benchmarks hallucination monitoring and output labelling pipelines.
• Sprint delivery and production reliability. Weekly quality scorecard.
• Hiring performance management and coaching.

You Must Have

• 7 years in software engineering with 3 years managing teams delivering AI/ML or LLM-powered products in enterprise production.
• Hands-on experience with LLM orchestration frameworks (LangGraph LangChain or equivalent) and multi-step agentic workflows.
• Strong grasp of RAG architecture: document pipelines chunking embedding vector databases re-ranking and similarity thresholds.
• Experience with managed inference infrastructure: AWS Bedrock SageMaker or equivalent.
• Track record shipping AI product features on schedule in a SaaS context not just prototypes or internal tools.
• Familiarity with AI observability: prompt tracing hallucination detection and output evaluation (Langfuse Ragas or equivalent).
• Data-driven: model evaluation scores accuracy/recall metrics agent success rates and DORA metrics for the team.
• Strong engineering standards: prompt discipline eval-driven development responsible AI controls and production-grade reliability.

Nice to Have

• Knowledge graph architectures (AWS Neptune Neo4j) for grounding agent outputs in structured asset data.
• Industrial domain knowledge: EAM ERP integrations (SAP Maximo) maintenance workflows or field operations.
• Multi-agent orchestration patterns: tool calling agent-to-agent delegation and human-in-the-loop checkpoints.
• Vision models or multimodal AI: image-based defect detection document OCR or form digitisation.
• MLOps and LLMOps: model versioning A/B evaluation and continuous prompt optimisation pipelines.
• Cloud cost optimisation for LLM workloads: token budgets model tiering and caching strategies.
• MongoDB and change stream-based event architectures.

Tech Stack & Tools

Compensation & Growth

Reports to VP PE&A. Path to Sr. EM or platform leadership as integration becomes a core horizontal capability.

What We Offer

• Competitive compensation and equity tied to measurable impact on AI accuracy and performance.
• A platform to shape the semantic intelligence layer of a category-defining industrial SaaS company.
• Access to cutting-edge AI data and observability toolchains for continuous learning and innovation.

Innovapptive does not accept and will not review unsolicited resumes from search firms.
Innovapptive is an equal opportunity employer and is committed to a diverse and inclusive workplace. Qualified applicants will receive consideration for employment without regard to race color religion or creed alienage or citizenship status political affiliation marital or partnership status age national origin ancestry physical or mental disability medical condition veteran status gender gender identity pregnancy childbirth (or related medical conditions) sex sexual orientation sexual and other reproductive health decisions genetic disorder genetic predisposition carrier status military status familial status or domestic violence victim status and any other basis protected under federal state or local laws