Technology Consulting - Digital - Forward Deployed Engineer - Manager

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Position Title: Manager - Forward Deployed Engineer (FDE)

Experience: 10+ years

 

Role Purpose

Design, build, deploy and optimize AI-enabled solutions directly within customer environments to accelerate business value realization. The role combines software engineering, solution architecture, AI implementation, and customer engagement responsibilities. The expectation is to be highly hands-on, working alongside customers and internal engineering teams to design, validate, deploy, and operationalize scalable AI, data, and cloud-native solutions rather than acting solely as an advisor.

 

Key Responsibilities

• Partner closely with customer stakeholders to understand business objectives, operational challenges, and technical requirements.
• Design and deliver end-to-end AI-enabled solutions, integrating enterprise systems, data platforms, APIs, and cloud services.
• Develop proof-of-concepts, prototypes, accelerators, and production-ready solutions to address customer-specific use cases.
• Implement and optimize LLM-powered applications, RAG architectures, agentic workflows, AI tool integrations, and workflow orchestration solutions.
• Build data ingestion, processing, and integration pipelines across structured and unstructured data sources.
• Work directly with customer engineering teams to troubleshoot, optimize, and scale deployed solutions.
• Collaborate with product, engineering, AI, security, and platform teams to translate customer requirements into reusable platform capabilities and product enhancements.
• Establish implementation patterns, deployment frameworks, observability mechanisms, and operational best practices.
• Ensure solutions adhere to security, compliance, scalability, reliability, and maintainability requirements.
• Provide technical leadership during customer engagements and contribute to architecture reviews, design validation, and solution governance.
• Document reusable patterns, reference implementations, and lessons learned to improve future deployments.

 

Required Skills and Experience

• Strong software engineering experience using Python, Java, C#, JavaScript, or TypeScript.
• Experience designing and deploying cloud-native applications on Azure, AWS, or Google Cloud Platform.
• Expertise in API design, microservices, distributed systems, event-driven architectures, and system integrations.
• Experience with containerization, Kubernetes, DevOps practices, CI/CD pipelines, and infrastructure automation.
• Knowledge of data engineering concepts including ETL/ELT, data pipelines, data lakes, streaming architectures, and API integrations.
• Experience building AI-enabled applications utilizing LLMs, RAG frameworks, vector databases, semantic search, and AI workflow orchestration.
• Understanding of AI evaluation, observability, guardrails, prompt engineering, and human-in-the-loop design patterns.
• Strong knowledge of software security, including IAM, API security, data protection, secrets management, and secure development practices.
• Experience troubleshooting and resolving complex technical challenges in production environments.
• Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.

 

Expected Profile

• The candidate must be hands-on, customer-facing, delivery-oriented, and capable of working effectively across engineering, product, data, AI, and business teams.
• The expectation is not only to design solutions but also to actively build, deploy, validate, and optimize them in real-world customer environments. The ideal candidate combines the technical depth of a Software Engineer, the problem-solving mindset of a Solution Architect, and the customer engagement skills of a Technology Consultant.
• They should be comfortable operating in ambiguous environments, rapidly understanding customer needs, developing practical solutions, and driving successful adoption of AI and digital technologies at enterprise scale.

 

 

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