Forward Deployed Engineer (FDE)

Ascendion; Bengaluru; On-site; INR 1,800,000 - 2,700,000; Full time

Job summary

Ascendion is seeking an experienced AI engineer in Bengaluru to drive end-to-end AI applications, leveraging Deep GenAI, RAG, and Knowledge Graphs. You will build multi-agent orchestration, tool use, memory, and human-in-the-loop capabilities, deploying production-grade solutions with Python and cloud platforms.

The role requires hands-on ML, MLOps practices, and strong data-architecture skills, with collaboration across business leaders and engineers to advance AI strategy.

Qualifications

• Experience with GenAI/Agentic AI in enterprise settings.
• Hands-on Python for AI applications and production deployments.
• Experience with architecture of large-scale data pipelines.

Responsibilities

• Develop multi-agent orchestration, tool use, memory, and human-in-the-loop capabilities.
• Lead end-to-end AI application development including APIs and production deployments.
• Define AI strategy, roadmaps, reference architectures, and best practices.
• Collaborate with executives and mentor engineers.

Skills

GenAI experience

Agentic AI

RAG/Knowledge graphs

Python

Full-stack AI apps

ML forecasting/anomaly detection

MLOps

Azure/GCP/AWS

Kubernetes

Data architecture

AI strategy

Stakeholder leadership

Education

Bachelor's/Master's in CS/AI

Tools

Azure

GCP

AWS

Kubernetes

Job description

• Utilize Deep GenAI and Agentic AI experience, especially in RAG, GraphRAG, Knowledge Graphs, and semantic search.
• Develop multi-agent orchestration, tool use, memory, and human-in-the-loop capabilities.
• Engage in full-stack AI application development with APIs, backend, and production deployments using Python.
• Build document ingestion and intelligent document processing pipelines.
• Apply ML background in forecasting, prediction, anomaly detection, and fraud/analytics use cases.
• Work hands-on with Azure, GCP, and ideally AWS, including AI/ML services and Kubernetes.
• Implement MLOps/LLMOps practices for model lifecycle, monitoring, governance, explainability, and production readiness.
• Demonstrate strong data architecture skills in large-scale pipelines, complex schemas, event-driven systems, APIs, and high-volume processing.
• Define AI strategy, roadmaps, reference architectures, standards, and best practices.
• Collaborate with business leaders and executives, mentor engineers, and contribute to technical design.
• Take ownership of work end-to-end with minimal supervision.
• Preferably have experience in finance/banking or regulated environments.
• Exhibit strong communication, stakeholder management, and cross-functional leadership skills.
• Strong Python skills for AI application development.
• Proficiency in ML for forecasting, prediction, anomaly detection, and fraud/analytics.
• Hands-on experience with Azure, GCP, and ideally AWS.
• Knowledge of MLOps practices and model lifecycle.
• Strong data architecture skills for large-scale pipelines and event-driven systems.
• Ability to define AI strategy, roadmaps, and best practices.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field.