Staff Data Scientist - Agentic AI

Posted 4 Days Ago
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Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Sales • Software
Salesloft helps thousands of the world’s most successful selling teams drive revenue with the Modern Revenue Workspace™
The Role
Build and operate production AI agents: define agent architecture, implement reasoning/execution loops, tool-harness, memory, planning, guardrails and evaluation. Integrate ML/time-series revenue models, lead system design, mentor peers, and partner cross-functionally to deploy reliable agentic workflows at enterprise scale.
Summary Generated by Built In

Job Title: Staff Data Scientist, Agentic AI

Location: Bengaluru, Hybrid

This is a hybrid position, which will require the ability to be onsite in our Bengaluru, India office as needed. Candidates must be based in India.

ABOUT THE COMPANY:

Clari + Salesloft are building the next era of enterprise revenue — one where teams make confident decisions powered by AI and real signals. By combining our scale, insights, and AI innovation, we’re building the industry’s first Predictive Revenue System, enabling humans and AI to work together to make smarter decisions and drive consistent growth.

With thousands of customers using our platforms every day, we have an unmatched view into how revenue is actually won — the Revenue Context that reveals what happens, when, and with what outcome. This gives us a unique opportunity to transform an entire category and set a new benchmark for how modern revenue teams operate.

Join us to help transform how companies around the world run revenue — and build the platform that will guide leading revenue teams into the future.

THE OPPORTUNITY:

At Salesloft, our Staff Data Scientist will be a hands-on builder of production AI agents - not a researcher who experiments with agent frameworks on the side. You will be a key member of our fast-growing, high-performing team in India, owning the components that turn an LLM call into a reliable, autonomous system that can reason, act, and recover in production. 

On a day-to-day basis, you will be responsible to -

  • Agent Architecture & Technical Strategy: Define the roadmap for our agentic AI stack => the execution loop, harness, memory, and tool/skill layers. And decide when an agent, a classical model, or a hybrid is the right tool for a given revenue problem.
  • Production Agent Engineering: Build and operate the core components of our agents end-to-end: the reasoning/execution loop, the harness that manages tool calls, retries, timeouts and session state, short- and long-term memory, and the skill/tool registry agents draw on (via MCP-style tool calling).
  • Planning & Multi-Step Reasoning: Design task-decomposition and planning strategies (evidence-based planning, plan-execute, multi-hop reasoning, research and many more) so agents can coach sellers, inspect deals, raise Forecast risks, update CRMs autonomously and correctly, and perform next best action to save the opportunity from slipping and many more.
  • Guardrails, Trust & Evaluation: Own the evaluation framework for agentic behavior - offline eval, LLM-as-judge, and online A/B testing plus the guardrails (input/output validation, policy and safety checks) that keep agents reliable at enterprise scale.
  • GenAI & Revenue Modeling: Apply rigorous statistical and time-series methods to our core revenue models (Forecasting, Deal Health, Risk Prediction), and connect them into agentic workflows where appropriate.
  • Multi-Agent & Cross-System Coordination: Design how agents talk to sub-agents and other systems (Agent-to-Agent style communication, tool/skill registries shared across agents), so capability is composed rather than rebuilt per use case.
  • Cross-Functional Technical Leadership: Partner with Product and Engineering leadership to translate business objectives into concrete agent designs, and serve as the technical anchor who can explain agent behavior and failure modes to non-technical stakeholders.
  • Mentorship & Culture: Mentor senior data scientists on agent-building discipline — not just prompting — and foster a culture of rapid experimentation paired with production rigor.
  • Enablement: Contribute to internal documentation, onboarding, and training on our agent components and patterns, promoting platform adoption across teams.

In addition to working with amazing colleagues who exemplify our ‘team over self’ core value, you will also have the opportunity to work on impactful and revolutionary software that is changing the way sellers sell. You will have an opportunity to make a difference. 

WHAT WE’RE LOOKING FOR:

We are seeking a Staff Data Scientist who has already spent real time building agents in production - someone who has hit the hard edges of memory, tool-calling, and reliability at scale, and knows how to design around them. If you're looking for an opportunity to learn more, do more, and become more by working alongside a highly motivated and skilled team and to own the agentic core of an enterprise AI platform, this is the career path for you.

THE TEAM:

Salesloft’ s goal is to build the world's first AI driven Predictive Revenue System. The Applied AI Engineering team is at the core of it to supply the AI platforms that are needed to build AI driven products.

The Engineering Team at Clari + Salesloft is deeply committed to building an enterprise-grade platform that serves as the backbone for our customer's most critical business process - Revenue. With an unrelenting commitment to innovation, our mission is to craft the ultimate revenue intelligence platform for our customers. Rooted in Agile principles, we foster a culture of adaptability and efficiency across all our teams. If you're energized by the prospect of contributing to a dynamic environment that emphasizes collaboration, continuous improvement, and leveraging the forefront of technology to address customer needs, we would love to meet you.

THE SKILL SET:

  • Experience: 8+ years in Data Science or Machine Learning, of which at least 2-3 years must be hands-on building and operating production AI agents (Staff/Lead experience preferred).
  • Agentic AI - Component Depth: Practical, production experience.
  • Core ML & Stats: Deep expertise in Classical ML (XGBoost, Causal Inference), Time-Series Forecasting, and Deep Learning fundamentals - you understand the math behind the models, not just how to import libraries.
  • Generative AI Foundations: Proficiency with modern agent/LLM frameworks (LangChain, LlamaIndex, DSPy, or equivalent in-house harnesses), vector databases (Pinecone, ElasticSearch), and techniques like fine-tuning (PEFT/LoRA) and RAG optimization.
  • Engineering First: Confident in Python. You are open and skilled to write production-ready code (modular, tested, typed).
  • System Design for Agents: Ability to design end-to-end agentic systems and articulate trade-offs between reasoning depth, latency, cost per agent turn, and reliability - and make architectural decisions that hold up at enterprise scale.
  • Education: MS or PhD in Computer Science, Statistics, Physics, Math, or an equivalent quantitative field is preferred.

Mandatory for this role -

  • 2-3 years of hands-on experience building and deploying AI agents in production — not experimenting with agent frameworks, building demos, or wrapping a single prompt with a tool call.
  • Demonstrated ownership of multiple agent components: the reasoning/execution loop, the harness (tool-calling, retries, timeouts, session/state management), memory (short-term context + long-term/episodic), the skill or tool registry, planning/task-decomposition, guardrails, and evaluation.
  • A distinct, verifiable data science or ML background (statistics, modeling, or applied ML) prior to or alongside the agent work - this is a Staff Data Scientist role, not a pure agent/backend engineering role.

At Clari + Salesloft, we are committed to creating an inclusive and supportive workplace where everyone belongs and can thrive. We focus on culture add, not culture fit, and believe our teams are made stronger by the unique perspectives, experiences, and identities each person brings.

We are proud to be an Equal Opportunity Employer and provide employment opportunities to all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, pregnancy, or any other characteristic protected by law.

If you’re excited about this role even though your experience may not perfectly match every requirement, we encourage you to apply. We are actively hiring across multiple geographies and would love to welcome passionate, curious, and mission-driven individuals to our growing team. Explore our open roles and consider joining us!

#LI-Hybrid

Please note that all official communication regarding job opportunities at Clari + Salesloft will come from an @clari.com  or @ salesloft.com email address. If you receive messages on LinkedIn or other job platforms claiming to be from Clari + Salesloft, they may not be legitimate. To verify the authenticity of any job-related communication, please visit our official Careers Page.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, notetaking, or summarizing responses. These tools assist our recruitment team but do not replace human judgment — all hiring decisions are made by people. If you would like more information about how your data is processed or prefer to opt out of any AI-assisted tools, please let your recruiter know. Opting out will not impact your experience or consideration.

Skills Required

  • 8+ years in Data Science or Machine Learning
  • 2-3 years hands-on experience building and deploying AI agents in production
  • Demonstrated ownership of agent components: execution loop, harness (tool-calling, retries, timeouts, session/state), memory, skill/tool registry, planning, guardrails, evaluation
  • Production-ready Python development (modular, tested, typed)
  • Proficiency with modern agent/LLM frameworks (LangChain, LlamaIndex, DSPy or equivalent)
  • Experience with vector databases (Pinecone, ElasticSearch)
  • Experience with fine-tuning and retrieval-augmented generation techniques (PEFT/LoRA, RAG optimization)
  • Core ML and statistics expertise (XGBoost, causal inference, time-series forecasting, deep learning fundamentals)
  • Ability to design end-to-end agentic systems and make trade-offs for latency, cost, and reliability at enterprise scale
  • Must be based in India and able to work hybrid with onsite presence in Bengaluru as needed
  • MS or PhD in Computer Science, Statistics, Physics, Math, or equivalent quantitative field

Salesloft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Salesloft and has not been reviewed or approved by Salesloft.

  • Leave & Time Off Breadth Time off is described as flexible and untracked with many company‑wide days, including a shutdown week and designated rest days. This breadth is positioned as a strong pillar of the total rewards offering.
  • Parental & Family Support Paid parental leave is characterized as substantial, with added supports like diaper subscriptions, meal stipends, and phased return‑to‑work. Access to fertility and family planning resources further strengthens this area.
  • Healthcare Strength Medical, dental, and vision options are paired with employer HSA funding and multiple mental‑health and wellness programs. The overall package is depicted as solid and competitive for U.S. roles.

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The Company
HQ: Atlanta, GA
704 Employees
Year Founded: 2011

What We Do

Salesloft is the provider of the leading sales engagement platform that helps sellers and sales teams drive more revenue. The Modern Revenue Workspace™ by Salesloft is the one place for sellers to execute all of their digital selling tasks, communicate with buyers, understand what to do next, and get the coaching and insights they need to win. Thousands of the world’s most successful sales teams, like those at IBM, Shopify, Square, and Cisco, drive more revenue with Salesloft. For more information visit salesloft.com.

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