AI Forward Deployment Engineer

EXL

Forward Deployment Engineer at EXLdata.ai responsible for deploying and supporting clients' cloud infrastructures. Focused on driving value realization and customization for client-specific needs.

Posted 6/30/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in deploying cloud infrastructure solutions using AWS, Azure, or GCP, alongside strong hands-on experience with data engineering tools such as PySpark, SQL, and Databricks. Capable of driving client-specific enhancements and delivering measurable outcomes through effective communication and collaboration.

Highest-signal resume keywords

AWS Cloud ServicesAzure Cloud ServicesGCP Cloud ServicesPySparkDatabricks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonKubernetesDockerCI/CDCloud Data ServicesIAMVPCAPI ManagementData Pipeline Management

Soft Skills

Strong Communication SkillsConsulting MindsetOwnership MentalityTeam CollaborationCustomer-First Orientation

Tools & Technologies

SnowflakeKinesisGlueRedshiftSynapseBigQueryDataProcLangChainLangGraphCrewAI

Industry Keywords

Data EngineeringCloud InfrastructureAutomationAI GovernanceClient Support

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureBigQueryCloudDockerGoogle Cloud PlatformKubernetesPySparkPythonSQL

About the role

Key responsibilities & impact

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
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.

Requirements

What you’ll need

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
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.
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.
“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.

Benefits

Comp & perks

EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.