EXL

Analyzes business data and runs outsourced operations

Data Scientist

Implementation & Technical Account ManagementConfirmed live in the last 24 hours

Full-timeNoida, Uttar Pradesh, IndiaNo salary listedIn-person

About the Job

Requirements

Four to six years of experience in Conversational AI, agentic development, or virtual-assistant development, including platforms such as Dialogflow CX, Amelia, Kore.ai, Rasa, or LLM-based agents.
One to two years of hands-on Sierra experience and at least one delivered or production Sierra project.
Strong programming background in TypeScript or JavaScript.
Experience with Agent Studio conversational design, customer journeys, and its block-based editor, including Journeys, Conditions, Rules, Policies, Tools, and Configuration.
Experience with Agent SDK development using TypeScript or JavaScript with JSX, including SDK APIs such as hooks, tool registration, and lifecycle events, code-defined simulations, and workspace, snapshot, and release concepts.
Ability to write instruction-driven and scenario-based simulations, enforce critical-simulation requirements, and stabilize flaky simulations.
Experience with Git and CI/CD, including branching, merging, code reviews, running simulations, and release enforcement in pipelines.
Bachelor's or Master's degree in Engineering.

Responsibilities

Build and validate agents in Agent Studio using Journeys, Conditions, Rules, Policies, Tools, and Configuration.
Implement code-defined agent behavior in the Agent SDK using TypeScript or JSX on Sierra's custom runtime, including hooks, tool registration, and lifecycle events.
Author instruction-driven and scenario-based simulations in Studio and code, and keep them stable and meaningful.
Integrate agents with APIs and enterprise or contact-center systems, including transfer and routing to queues and numbers with attached data.
Participate in workspace-based development through merge requests, snapshots, and workspace reviews.
Execute releases under guidance while respecting critical-simulation gates and approvals.
Contribute to CI/CD, including running simulations and wiring release checks.
Design and develop data models and analytical solutions.
Optimize data analysis processes and methodologies.
Ensure data solutions meet business and technical requirements.
Provide technical support for data science projects.
Collaborate with stakeholders to address data science needs.

Desired Qualifications

Experience with Ghostwriter AI-assisted authoring, including prompting, reviewing, validating, and merging AI-generated journeys and simulations.
Basic observability experience with traces and alerts, and analytics such as CSAT and resolution or containment rate.
Exposure to contact-center or IVR systems and telephony transfer, such as Genesys or similar.

Band B1 / B2 — Sierra Engineer

Experience

4–6 years total in Conversational AI / agentic or virtual-assistant development (e.g., Dialogflow CX, Amelia, Kore.ai, Rasa, LLM-based agents).
1–2 years hands-on Sierra, with at least one delivered/production Sierra project.
Strong programming background in TypeScript / JavaScript.

Core Responsibilities

Build and validate agents in Agent Studio using Journeys, Conditions, Rules, Policies, Tools, and Configuration.
Implement code-defined agent behaviour in the Agent SDK (TypeScript/JSX on Sierra's custom runtime) using hooks, tool registration, and lifecycle events.
Author instruction-driven and scenario-based simulations (Studio and code) and keep them stable and meaningful.
Integrate agents with APIs and enterprise/contact-centre systems, including transfer/routing to queues and numbers with attached data.
Participate in workspace-based development: merge requests, snapshots, and workspace reviews.
Execute releases under guidance, respecting critical-simulation gates and approvals.
Contribute to CI/CD (e.g., GitHub Actions) — running simulations and wiring release checks.

Mandatory Skills (per Sierra platform)

Agent Studio: conversational design, customer journeys, and the block-based editor (Journeys, Conditions, Rules, Policies, Tools, Configuration).
Agent SDK: TypeScript/JavaScript with JSX; SDK APIs (hooks, tool registration, lifecycle events); code-defined simulations; workspace/snapshot/release concepts.
Simulations: writing instruction-driven and scenario-based tests; critical-simulation enforcement; stabilising flaky simulations.
Git & CI/CD: branching, merging, code reviews; running simulations and release enforcement in pipelines.

Good to Have

Ghostwriter (AI-assisted authoring): prompting, reviewing, validating, and merging AI-generated journeys/simulations.
Basic observability (traces/alerts) and analytics (CSAT, resolution/containment rate).
Contact-centre / IVR and telephony transfer (Genesys or similar) exposure.

Bachelor's/Master's in Engineering 2-5 years

Design and develop data models and analytical solutions, Optimize data analysis processes and methodologies, Ensure data solutions meet business and technical requirements, Provide technical support for data science projects, Collaborate with stakeholders to address data science needs.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1999

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