Role Overview
The Forward Deployment Engineer (FDE) is the tip-of-the-spear technical role responsible for ensuring that EXLdata.ai is successfully deployed, adopted, and scaled within client environments.
You will work side-by-side with client teams, product engineering, and our GenAI agent teams to:
- Deploy EXLdata.ai into client cloud infrastructure (AWS/Azure/GCP)
- Resolve infra, security, and data pipeline issues in real time
- Customize accelerators and agent workflows for client-specific needs
- Drive measurable value realization from Day 1
- Champion product enhancements back to the EXLdata.ai engineering team
- Deliver white-glove support for clients using our managed platform offering
This role is ideal for a senior data engineer who loves solving real-world problems, can operate in ambiguous conditions, learns fast, and thrives in high-impact client environments.
About EXLdata.ai
EXLdata.ai is EXL’s flagship multi-agent orchestration platform that automates the end-to-end lifecycle of enterprise data pipelines – spanning data migration, data engineering, data quality, data governance, data ops, and unstructured data annotation.
Having launched our MVP and now expanding across multiple Fortune-500 engagements, we are entering a rapid scale-up phase with two distinct delivery models:
1. Client-Deployed Model: Deploy EXLdata.ai within the client’s own cloud (AWS/Azure/GCP) and orchestrate their pipelines using our accelerator suite.
2. Managed Platform Model: EXL hosts EXLdata.ai in a dedicated private cloud and provides a white-glove, Data-Product-as-a-Service experience.
To support this growth, we are hiring a Forward Deployment Engineer who will serve as the technical anchor at the intersection of cloud engineering, data engineering, GenAI, and client value realization.
Key Responsibilities
1. Deployment & Infrastructure Engineering
- Deploy EXLdata.ai in client-owned AWS/Azure/GCP environments.
- Configure networking, security, CI/CD, Kubernetes, API gateways, and identity integration.
- Troubleshoot environment, infra, IAM, and pipeline-related issues.
- Lead cloud-level optimizations (scaling, cost, performance tuning).
2. Data Engineering & Pipeline Enablement
- Build, customize, and optimize data pipelines using PySpark, SQL, Databricks, Snowflake, or native hyperscaler data services.
- Integrate platform agents into client workflows (Data Migration, DQ, DataOps, Annotation).
- Assist client SMEs in onboarding data sources, targets, and transformations.
3. Value Realization & Client Enablement
- Serve as the technical anchor for first-of-kind deployments at each client.
- Ensure clients see measurable value from agent-driven automation (SLA reduction, pipeline acceleration, DQ uplift, migration speed).
- Provide hands-on support across discovery, configuration, runbooks, and UAT.
4. GenAI Agent Integration
- Work with product engineering on integrating new GenAI agents into client pipelines.
- Tailor agent behaviors, triggers, and workflows for domain-specific use cases.
- Share field insights that shape our agent roadmap.
5. Product Innovation & Feedback Loop
- Act as the “voice of the customer” for the EXLdata.ai product team.
- Identify enhancements, feature gaps, and new accelerator ideas.
- Participate in internal sprints, tooling improvements, and platform hardening.
6. Managed Service / White-Glove Model
- Support deployments in EXL-hosted private cloud environments.
- Serve as the first line of operational excellence for premium clients.
- Lead operational reliability, monitoring, and support SLAs.
Expertise
- 6–12+ years as a Senior Data Engineer, Forward Deployment Engineer
- Strong hands-on experience with at least one hyperscaler (AWS or Azure or GCP).
- Deep expertise in:
- PySpark, SQL, Python
- Databricks / Snowflake (one mandatory, both preferred)
- Cloud data services (Kinesis, Glue, Redshift, Synapse, BigQuery, DataProc, etc.)
- Kubernetes, Docker, CI/CD
- IAM, VPC, private networking, secrets, API management
Delivery & Client Facing Skills
- Demonstrated ability to work directly with client engineering teams.
- Comfortable running design discussions, debugging sessions, and deployment workshops.
- Strong communication skills; able to simplify technical topics for business audiences.
- Ability to operate independently with a consulting mindset and ownership mentality.
GenAI & Multi-Agent Curiosity
- Exposure to LLMs, agent tooling (LangChain, LangGraph, CrewAI, etc.), or willingness to learn fast.
- Strong interest in how AI can automate data engineering and governance.
Base Compensation Range: 125,000-175,000
- The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.
Skills Required
- 6-12+ years as a Senior Data Engineer or Forward Deployment Engineer
- Hands-on experience with at least one hyperscaler (AWS or Azure or GCP)
- PySpark, Python, SQL
- Databricks or Snowflake (at least one mandatory)
- Experience with cloud data services (Kinesis, Glue, Redshift, Synapse, BigQuery, DataProc, etc.)
- Kubernetes, Docker, CI/CD
- IAM, VPC, private networking, secrets management, API gateways/API management
- Ability to troubleshoot infrastructure, security, and data pipeline issues in real time
- Client-facing delivery skills, strong communication, consulting mindset and ownership
- Exposure to GenAI/LLMs and agent tooling (LangChain, LangGraph, CrewAI) or willingness to learn
- Experience with both Databricks and Snowflake
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
