Senior AI Forward Deployed Engineer - Cogentiq I2C
Fractal Analytics16 days ago
Mumbai, India or Bengaluru, IndiaStaff+
Responsibilities
- Own the technical outcome and customer relationship for a portfolio of accounts from discovery through production rollout and scale.
- Define and defend deployment KPIs covering accuracy, straight-through processing, latency, cost, adoption, and business impact.
- Design AI agent topology, retrieval strategy, human oversight boundaries, integration approach, and data models.
- Make and document build-versus-configure-versus-product-extension decisions and own ERP, banking, and document infrastructure integrations.
- Lead and develop a deployment team, including scoping, sequencing, estimates, success criteria, and blocker removal.
- Act as incident commander for production failures and own root-cause analysis and remediation.
- Advise finance and IT leaders on system capabilities, residual risk, governance, model risk, human oversight, and responsible AI.
- Convert deployment learnings into reusable architectures, connector templates, evaluation packs, and deployment accelerators.
- Provide evidence-based customer feedback to the product roadmap and distinguish product gaps from customer-specific preferences.
Requirements
- 6 to 10 years of experience building and operating production systems, including at least two years in customer-facing delivery.
- A track record of taking at least one non-trivial AI system to production and operating it afterward.
- Strong Python and system design skills.
- Depth in LLM and agentic architectures, retrieval, evaluation methodology, guardrails, and observability.
- Cloud deployment experience at scale, with Azure preferred.
- Experience with containers and orchestration.
- Ability to discuss finance concepts including DSO, deductions, remittance advice, and cash application, or learn them within a quarter.
- Commercial judgment, including recognizing and escalating unpaid customer scope.
- Willingness to travel and embed with customers.
- Preferred: AI deployments in regulated industries, enterprise ERP integration, SAP S/4HANA or Dynamics 365 Finance and Operations experience, engineering mentorship or leadership, pre-sales or solution architecture exposure, and startup or product-building experience.