Forward Deployed AI Engineer New New York, NY

Indicium; New York (NY); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive pay with performance bonus

Comprehensive health coverage

Generous PTO

Job summary

Indicium AI in New York City is seeking a Senior Forward Deployed AI Engineer to bridge enterprise data estates with frontier agentic AI execution. You will embed with client leadership to translate complex data into production-grade multi-agent platforms, real-time context retrieval systems, and LLM evaluation architectures.

You will own architecture reviews, PoCs, and on-site collaboration, delivering high-agency solutions with attention to runtime business impact and strict security controls.

Qualifications

• Proven production multi-agent systems experience.
• 2],

Responsibilities

• Architect and deploy MCP-based agentic tooling and data interfaces.
• Build high-performance data pipelines and retrieval layers over lakehouse environments.

Skills

Agentic AI

Data engineering

Lakehouse

Client-facing

Education

MS/PhD in CS/ML

Tools

Databricks

PySpark

Delta Lake

SQL

Python

LangGraph

AutoGen

CrewAI

Job description

Forward Deployed Software Engineer — US / NYC

About Indicium AI

Indicium AI was Anthropic’s first European launch partner, a Preferred Anthropic Partner, and sits among a handful of organizations globally trusted to deploy Claude at an enterprise scale. Named the2026 Databricks Consulting Partner of the Year and backed by Databricks Ventures, we build and deploy production AI systems for complex enterprises, making AI a genuine competitive advantage.

The Role

The Senior Forward Deployed AI Engineer, Data Platform & Agents bridges the gap between complex enterprise data estates (Databricks, Lakehouses, vector stores) and frontier agentic AI execution (Anthropic Claude, multi-agent frameworks, custom MCP servers). Sitting embedded directly with client CDOs, VPs of Data, and engineering leadership, you will translate messy operational workflows and fragmented data sources into production-grade multi-agent platforms, real-time context retrieval systems, and LLM evaluation architectures.

This is a high-agency "builder-consultant" role for engineers who care as much about stakeholder adoption and runtime business impact as they do about model accuracy, protocol design, and low-latency data execution.

Key Responsibilities

Agentic Tooling & MCP Architecture: Architect and deploy custom data interfaces and tool servers using theModel Context Protocol (MCP), function calling, and structured JSON schemas—enabling autonomous AI agents to query, synthesize, and execute actions across 10+ disparate enterprise data sources safely.

Enterprise Lakehouse & Retrieval Engineering: Build high-performance datapipelines, vector search, and hybrid RAG layers over Lakehouse environments (Databricks, PySpark, Delta Lake, Unity Catalog)—slashing retrieval times and optimizing CPU/GPU query runtimes over massive structured and unstructured datasets.

Embedded Client Execution & PoCs: Sit side-by-side with client technical teams to run daily requirements discovery, lead architecture reviews, and rapidly ship zero-to-one production Proofs of Concept (PoCs) in weeks rather than months.

LLM Evals, Observability & Guardrails: Implement robust evaluation frameworks (LLM evals, hallucination tracking, retrieval precision/recall) and observability pipelines to monitor non-deterministic agent behavior and guarantee reliability in strictly regulated enterprise environments (Financial Services, Healthcare).

Enterprise Security & Data Isolation: Collaborate with client CISO and security governance teams to enforce strict access-control lists (ACLs), multi-tenant isolation, row/column-level permissions, and zero-data-leakage constraints.

Qualifications & Experience

Agentic AI & Orchestration: Proven track record building and deploying production multi-agent systems, RAG platforms, and MCP servers using frameworks like LangGraph, AutoGen, or CrewAI.

Data Engineering & Lakehouse Depth: 5+ years of experience withDatabricks, PySpark, Delta Lake, SQL, and Python—with specific expertise optimizing high-QPS analytical queries and processing unstructured enterprise documents (PDFs, contracts, logs).

Statistical Rigor & Model Evals: Strong foundation in quantitative methods, statistics, or applied ML (M.S./Ph.D. or equivalent industry experience) to evaluate model uncertainty, ground truth, and non-deterministic systems systematically.

Client-Facing / Consultative Muscle: Demonstrated ability to run technical discovery calls, manage non-technical client stakeholders, handle technical pushback, and lead co-engineering efforts on-site.

Why Indicium AI

Deep Anthropic Partnership: Work at the bleeding edge as a Preferred Anthropic Partner, with direct access to partner teams, official training, and early access to unreleased capabilities.

High Autonomy Culture: Sharp, high-agency teams with no middle-management layers or corporate theater.

Frontier-Level L&D: Generous learning budget, dedicated research time, and unencumbered access to state-of-the-art AI tools.

Top-Tier Benefits: Competitive pay with performance bonuses, comprehensive health coverage, generous PTO, flexible holidays, parental leave, and a paid company shutdown the last week of December.

The anticipated base salary range for this role is $180,000 - $240,000. In addition to base pay, this position may be eligible for an annual discretionary bonus. An individual's final salary offer will be determined based on a variety of factors, including geographic location, experience, specialized skills, and qualifications. This compensation range is subject to updates or modifications at the company’s discretion

As set forth in Indicium AI’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.