Senior AI Forward Deployed Engineer; FDE ; Eng

Overview

Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences tomorrow. A Service Now-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider.

You are a hands‑on architect who understands how to integrate Generative AI into complex, existing enterprise ecosystems. You possess strong Data Engineering skills and a grasp of Classical Machine Learning. You integrate GenAI into enterprise ecosystems involving legacy systems, complex data estates, and multi-step data pipelines.

Key Responsibilities:

• Complex System Integration:
  Integrate LLM solutions with legacy systems (ERPs, CRMs) and multiple data sources. Design systems that utilize Graph Databases or complex SQL queries alongside Vector Stores.
• Data Engineering:
  Build robust data pipelines (ETL/ELT) for GenAI strategies. Understand Map Reduce principles and data structure analysis.
• Hybrid AI Approach:
  Know when to use Classical Machine Learning (Regression, Classification) versus Generative AI.
• Data Strategy:
  Formulate data strategies for clients, selecting the right database types (RDB, No
  
  SQL, Graph, In-memory Cache) for the specific use case.
• Data governance:
  Implement lineage, PII handling, access control.
• Architecture:
  Build event‑driven architectures and multi‑agent orchestration.
• Testing:
  Strategize and conduct integration testing, regression testing, QA.
• Customer Guidance:
  Provide architectural guidance and educate customers.

Focus:
Systems Integration, Data Engineering & Complex Logic

Experience:

5–8 Years

• Data:
  Pandas, SQL optimization, Graph DBs (Neo4j), Vector Database internals.
• Integration:
  Event‑driven architecture, Enterprise Service Bus patterns, Multi‑agent orchestration.
• ML Knowledge:
  Understanding of statistics, classical ML algorithms, and data structure analysis.
• Security: IAM, governance, audit trails.

• Strong stakeholder management across engineering, data, and business.
• Ability to simplify complex technical concepts for non‑technical leaders.
• Solution‑oriented thinking under ambiguity.
• Mentorship and coaching of Lead and Junior FDEs.
• High empathy and customer‑centric design approach.