Architect, Forward Deployed Engineer (Cogentiq)

Fractal Analytics•New York, NY

4d•$150,000•Onsite

About The Position

Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Please visit Fractal | Intelligence for Imagination for more information about Fractal. Cogentiq is Fractal's Enterprise AI platform that enables organizations to build, deploy, and govern intelligent AI agents grounded in enterprise context. By connecting AI with enterprise knowledge, business systems, and workflows, Cogentiq empowers enterprises to solve complex business problems with trustworthy, scalable, and production-ready AI. We are looking for Forward Deployed Engineers (FDEs) to join the founding Cogentiq team. As an FDE, you will work at the intersection of software engineering, AI, enterprise integration, and customer success. You will partner closely with enterprise customers to understand their business challenges, design AI-powered solutions, build production-grade integrations, and deploy Cogentiq into complex enterprise environments. Beyond customer implementations, you'll help shape the evolution of the Cogentiq platform by transforming deployment learnings into reusable platform capabilities, connectors, and best practices. This role is ideal for engineers who enjoy solving ambiguous, real-world problems, thrive in fast-paced environments, and are excited to build the next generation of Enterprise AI.

Requirements

Strong Software Engineering fundamentals
Experience in building production-grade backend applications, REST APIs, microservices, and distributed systems
Proficient in working with databases, Git, and modern software development practices.
Proficient in Python
Hands-on experience building AI-powered applications using Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), tool calling, prompt engineering, and AI evaluation techniques.
Experience integrating enterprise applications and platforms such as SAP, Salesforce, Workday, ServiceNow, SharePoint, Snowflake, Databricks, and other business systems.
Experience with enterprise integration patterns, API-first architectures, authentication mechanisms such as OAuth, JWT, and SAML, and are proficient working with SQL, REST, and GraphQL APIs.
Experience building and deploying cloud-native applications on Azure, AWS, or Google Cloud using Docker and Kubernetes.
Experience with CI/CD pipelines, event-driven architectures, messaging platforms, observability, monitoring, and security best practices required to build reliable enterprise platforms.
Experience working directly with customers, understanding their business challenges and translating them into elegant technical solutions.
Communicating effectively with both technical and business stakeholders and are comfortable leading architecture discussions and technical workshops and thrive in environments where requirements evolve rapidly.
Experience in ownership of outcomes, learn quickly, prototype rapidly, and continuously look for opportunities to transform customer-specific solutions into reusable platform capabilities.

Nice To Haves

Experience in Java or TypeScript being a plus.
Experience with the Model Context Protocol (MCP) and modern AI orchestration frameworks is highly desirable.

Responsibilities

Design and develop production-grade AI applications using the Cogentiq platform.
Deploy enterprise AI solutions from proof of concept to production.
Build integrations with enterprise applications such as SAP, Salesforce, Workday, ServiceNow, SharePoint, Snowflake, Databricks, and other business systems.
Develop reusable connectors, APIs, SDKs, MCP servers, and automation components.
Design secure, scalable, cloud-native architectures and build reliable backend services and microservices.
Collaborate directly with customer engineering and business teams to understand requirements, conduct technical workshops, and deliver successful AI solutions.
Troubleshoot production deployments, optimize system performance, and ensure reliability and security.
Capture learnings from customer deployments and contribute reusable capabilities back to the Cogentiq platform.
Work closely with AI engineers, platform engineers, product managers, and solution architects to continuously improve the platform.