JOB DESCRIPTION
Location: US / Remote
Practice: EXLdata.ai – Multi-Agent Data Engineering Platform
Role Type: Client-Facing | High-Visibility | Strategic Delivery
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.
JOB 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.
JOB QUALIFICATIONS
Technical Expertise
- 6–12+ years as a Senior Data Engineer, Forward Deployment Engineer, or Platform 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.
Mindset & Attributes
- “Can-do” attitude; thrives in ambiguity.
- Fast learner; bias for action.
- Team player who collaborates across product, engineering, and client teams.
- Customer-first orientation and passion for delivering measurable outcomes.
