NLP Jobs in Chennai.
All active NLP roles based in Chennai.
Pick a job to read the details
Tap any role on the left — its description and apply link will open here.
Critically, this role sits at the intersection of data, AI, and people. The ideal candidate will be as comfortable enabling a frontline sales rep to understand and act on a dashboard as they are presenting strategic insight to a C-suite audience. They will also be a confident and curious adopter of large language model (LLM) tools — using AI to accelerate their own analytical workflow and helping the wider business do the same.
Key Responsibilities
- Business Analysis & Stakeholder Partnership
- Act as the primary analytics partner to senior commercial stakeholders across Sales, Marketing, Customer Success, and Revenue Operations.
- Apply strong business analysis discipline — translating ambiguous business questions into well-scoped requirements, clear success criteria, and structured analytical briefs before any build begins.
- Proactively surface insights, trends, risks, and opportunities that inform decision-making at leadership level.
- Support strategic initiatives such as CRM consolidation, demand intelligence optimization, territory and book-of-business changes, and forecasting improvements.
- Own end-to-end project management of analytics deliverables — from requirements gathering and prioritization through to delivery, adoption, and iteration — ensuring stakeholders are informed and timelines are met
- Communication, Enablement & Influence
- Demonstrate exceptionally strong communication skills across all levels of the organisation — from crafting executive narratives for senior leadership forums to running hands-on enablement sessions for managers and frontline sales representatives.
- Translate complex data, AI outputs, and analytical findings into plain-language stories that drive clarity, confidence, and action.
- Design and deliver enablement programmes that help managers and reps understand, trust, and act on dashboards, KPIs, and AI-generated insights — building genuine data literacy across the Revenue Organisation rather than dependency on the BI team.
- Champion clear, consistent communication of what metrics mean, how they are calculated, and why they matter — removing ambiguity at every level.
- Influence without authority; build credibility with senior stakeholders through the quality of insight and the integrity of the underlying data.
- Analytics, Reporting & Insight
- Own the design and delivery of executive-level dashboards and self-service reporting, primarily using Power BI.
- Ensure consistent definitions and calculations for revenue KPIs, North Star metrics, and commercial performance indicators.
- Conduct deep-dive analyses to diagnose performance issues and recommend actionable next steps.
- Write and optimise advanced SQL queries to extract, transform, and validate data across our Databricks data warehouse and connected source systems.
- Leverage Databricks as the central analytical platform — working within notebooks, SQL warehouses, and the broader Lakehouse environment to build reliable, scalable analytical outputs.
- AI & LLM Integration
- Be a power user and internal advocate of LLM-based tools, including Microsoft Copilot and Anthropic Claude (including Claude Code), using them to accelerate analysis, generate and review SQL, draft communications, and surface insight more efficiently.
- Help define and create LLM agents for the Go To Market organisation – connecting context to frontline AI tools such as MS Copilot and Salesloft.
- Proactively identify opportunities to embed LLM and AI capabilities into BI workflows, dashboards, and analytical processes — raising the ceiling of what the team can deliver.
- Work with the Senior Manager of BI to evaluate and scale AI-assisted analytics approaches across the team, including the use of Databricks' native LLM and AI capabilities.
- Help commercial stakeholders and frontline teams understand and appropriately trust AI-generated outputs — building confidence in AI tools through clear explanation, demonstration, and enablement.
- Data Modelling & Quality
- Partner with Data Analytics Engineers to define analytical data models that support revenue, pipeline, customer lifecycle, and performance reporting.
- Validate data accuracy and integrity across the analytics layer, proactively identifying and resolving issues before they impact decision-making.
- Contribute to data governance standards, metric documentation, and reporting best practices.
- Technology & Tooling Context
-
- The Lead Business Analyst will work within a modern BI and revenue intelligence stack, including:
- Layer Tools
- Data Warehouse & Analytics Databricks (central data warehouse with LLM capabilities)
- BI & Visualisation Power BI
- AI & LLM Tooling Microsoft Copilot, Anthropic Claude, Claude Code, Databrick Genie, Databricks hosted LLM models
- Core Commercial Systems Salesforce (multiple instance), PlanHat, &
- Revenue & Demand
- Intelligence Clay
- Sales Enablement &
- Engagement Salesloft (including AI and conversational intelligence) & HighSpot
- A strong understanding of how these systems connect — and how data flows end-to-end from source systems to executive dashboards and frontline tools — is essential.
-
- Required Experience & Skills
-
- 8+ years of experience in a Business Analysis, Analytics, or BI within a SaaS or technology-driven organisation.
- Experience supporting RevOps, Sales Operations, or Commercial Analytics teams.
- Advanced SQL skills — comfortable writing complex queries, debugging data issues, and working directly within a cloud data warehouse environment; Databricks experience strongly preferred.
- Strong business analysis capability — proven ability to scope, structure, and document analytical requirements with rigour before moving into delivery.
- Proven project management skills — able to manage multiple concurrent workstreams, set and meet deadlines, and maintain clear stakeholder communication throughout.
- Exceptionally strong communication skills — a natural and compelling communicator in written and verbal form, equally effective presenting strategy to a VP as running a training session for a team of account executives.
- Demonstrated experience designing and delivering stakeholder enablement on data, dashboards, or analytics tooling — not just building outputs, but ensuring they are understood and adopted.
- Proven experience delivering executive-ready dashboards and self-service reporting (Power BI preferred).
- Strong commercial and revenue-focused business acumen.
- Active and confident user of LLM tools such as Microsoft Copilot or Anthropic Claude in a professional analytical context.
- Preferred Experience
-
- Hands-on experience with Databricks — including SQL warehouses, notebooks, and the Lakehouse architecture.
- Experience using Claude Code or similar AI coding assistants to accelerate SQL development, data validation, or analytical scripting.
- Familiarity with CRM and GTM analytics — Salesforce, pipeline reporting, forecasting, MEDDPICC, territory models.
- Hands-on Experience with Clay
- Ideally experience with Python (e.g. connecting to APIs)
- Exposure to building or scaling data literacy programmes within a commercial organisation.
- What Success Looks Like
- Leaders trust the dashboards and insights/recommendations produced and use them to run the business with confidence.
- Managers and frontline reps understand and act on data, insights, and AI outputs — because this role has invested in enabling them, not just building for them.
- KPIs and metrics are clearly defined, consistently applied, and widely adopted across the organisation.
- LLM and AI tools are meaningfully embedded into BI workflows, improving speed, quality, and reach of analytical output.
- The BI team is seen as a strategic partner — not just a reporting function.
- Data quality issues are proactively identified and resolved before impacting decision-making.
- Projects are delivered on time, with clear communication and minimal surprises for stakeholders.
Ready to apply?
Apply to Cision
Gen AI Lead
Share this job
Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
Role: GenAI Lead Engineer
Experience: 8+ years total (with significant hands-on GenAI / LLM work)
Job Overview:
We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.
Key Responsibilities:
- Technical Leadership:
- Lead the end-to-end design and implementation of Generative AI solutions.
- Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
- Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
- Solution Development:
- Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
- Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
- Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
- Ensure scalability, performance, and security of AI solutions deployed in production.
- Integration and Deployment:
- API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
- Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
- Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
- Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
- Data Strategy and Preparation:
- Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
- Implement data governance and privacy practices in line with organizational policies.
- Innovation and Research:
- Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
- Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
- Stakeholder Collaboration:
- Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
- Present technical concepts, project progress, and AI capabilities to non-technical audiences.
Key Requirements
- Technical Skills:
- Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
- Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
- Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
- Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
- Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
- Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
- Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
- Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
- 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
- Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
- Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
- Proven track record of leading AI projects from inception to production.
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
- Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
Candidate Privacy Policy
Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, “Orion,” “we” or “us”) are committed to protecting your privacy. This Candidate Privacy Policy (orioninc.com) (“Notice”) explains:
- What information we collect during our application and recruitment process and why we collect it;
- How we handle that information; and
- How to access and update that information.
Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.
Ready to apply?
Apply to Orion Innovation
About Tekion:
Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.
Role Overview
We are seeking a Principal Applied Scientist to be the highest-level AI technical authority on the team. This role is above the Applied Scientist level — you set the AI research and engineering direction, own the agentic system architecture, define the eval framework standards, and operate as the primary interface to the external AI research community and internal platform AI leadership. You will combine deep research rigor with relentless production focus: every AI capability you design ships, gets measured, and improves based on evidence.
You are the person who answers: "Is this AI approach the right one, and how do we know when it's working"
Key Responsibilities
- Own the agentic system architecture: define the multi-agent coordination patterns, MCP tool taxonomy, intent-to-skill routing logic, policy enforcement design, and memory management strategy across all AI workflows on the platform.
- Lead the AI evaluation framework: design the golden dataset structure, define eval metrics (RAG retrieval quality, scoring accuracy, LLM response correctness, agentic workflow success rate), and own the CI/CD AI eval pipeline that gates every AI capability release.
- Drive the RAG architecture strategy: chunking strategies for MongoDB and Elasticsearch-indexed documents, embedding model selection and fine-tuning, retrieval reranking design, and hallucination mitigation patterns.
- Own the LLM integration architecture: prompt engineering standards, LLM gateway usage policies, context window management, streaming response patterns, and model version governance.
- Lead applied research initiatives: identify novel techniques (RLHF, Constitutional AI, multi-modal, sparse retrieval) that are practically applicable to automotive retail intelligence use cases and prototype them rigorously in Python.
- Define the hexagonal AI adapter contract standard: the formal interface specification between Python AI services and Java domain cores — ensuring AI infrastructure remains swappable without domain logic changes.
- Act as primary technical interface to platform AI leadership (LLM Gateway, ML Platform, Agentic Engine) — influencing platform roadmap based on teams practical requirements.
- Mentor the Applied Scientist and ML Architect; conduct technical reviews of AI system designs, eval frameworks, and research approaches.
- Publish, present, or contribute to open-source where appropriate — representing Tekion's AI engineering excellence externally.
Skills & Qualifications
- 10+ years of applied AI/ML experience with at least 3 years at Staff or Principal level — a track record of shipping AI systems that measurably changed business outcomes.
- Deep expertise across: LLM fine-tuning and alignment, RAG system design (chunking, embedding, retrieval, reranking), agentic frameworks (LangGraph, CrewAI, AutoGen), and MCP tool design.
- Python mastery: PyTorch, Hugging Face Transformers, LangChain/LangGraph, scikit-learn, and production ML serving tooling.
- Strong understanding of distributed AI systems: Elasticsearch-backed vector search, Redis/Aerospike serving, Cosmos DB for AI event logging, and Kafka-based feature pipelines.
- Proven ability to design formal eval frameworks for AI systems — not just accuracy metrics but business aligned quality gates.
- Experience defining and enforcing hexagonal adapter contracts between AI services and domain service layers in production systems.
- Track record of communicating complex AI system design to non-technical stakeholders, influencing product roadmaps, and driving cross-team alignment.
Good to Have
- Publications or significant open-source contributions in NLP, information retrieval, or agentic systems.
- Experience with Constitutional AI, RLAIF, or preference optimization techniques (DPO, PPO).
- Familiarity with multi-modal AI and its application to automotive retail data (images, documents, tabular data fusion).
- Prior experience in a product-focused AI role at a SaaS or platform company — not purely research.
Perks & Benefits
- Competitive compensation and generous stock options.
- Medical insurance coverage.
- Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.
Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.
For more information on our privacy practices, please refer to our Applicant Privacy Notice here.
Ready to apply?
Apply to Tekion
Gen AI Lead
Share this job
Role: GenAI Lead Engineer
Experience: 8+ years total (with significant hands-on GenAI / LLM work)
Job Overview:
We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.
Key Responsibilities:
- Technical Leadership:
- Lead the end-to-end design and implementation of Generative AI solutions.
- Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
- Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
- Solution Development:
- Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
- Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
- Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
- Ensure scalability, performance, and security of AI solutions deployed in production.
- Integration and Deployment:
- API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
- Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
- Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
- Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
- Data Strategy and Preparation:
- Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
- Implement data governance and privacy practices in line with organizational policies.
- Innovation and Research:
- Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
- Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
- Stakeholder Collaboration:
- Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
- Present technical concepts, project progress, and AI capabilities to non-technical audiences.
Key Requirements
- Technical Skills:
- Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
- Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
- Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
- Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
- Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
- Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
- Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
- Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
- 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
- Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
- Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
- Proven track record of leading AI projects from inception to production.
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
- Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).
Ready to apply?
Apply to Orion Innovation Naukri
Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide.
Living our values everyday results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves.
About the Role
We are looking for a high-potential Product Manager Apprentice to join our Product Management team working on next-generation Contact Center as a Service (CCaaS) platforms. This role is designed for early-career professionals who are passionate about building enterprise SaaS products and want hands-on exposure to AI-driven customer experience technologies and modern cloud-native architectures.
As a Product Manager Apprentice, you will work closely with Product Managers, Engineering, UX, Data Science, and GTM teams to define, build, and scale features across our CCaaS product lines — including AI-powered voice, digital, analytics, automation, workforce management and integrations platforms.
This is a learning-intensive role that provides real ownership, structured mentorship, and exposure to the full product lifecycle in a fast-growing SaaS environment.
Key Responsibilities
Product Discovery & Strategy Support
- Assist in researching customer problems across contact center domains such as Inbound, outbound campaigns, agent experience, AI automation, analytics, Quality Management, Workforce Management, and integrations.
- Analyze market trends in CCaaS, AI in CX, cloud communications, and SaaS platforms.
- Support product managers in defining product vision, value propositions, and roadmap priorities.
AI & Data-Driven Product Development
- Work with AI/ML teams on features involving speech-to-text, NLP, LLMs, conversation intelligence, automation, and predictive analytics.
- Help translate AI capabilities into real-world customer use cases and measurable business outcomes.
- Contribute to defining product requirements for AI-enabled workflows and decisioning systems.
Requirements & Delivery Execution
- Assist in creating Product Requirement Documents (PRDs), user stories, and acceptance criteria.
- Work closely with engineering teams using Agile/Scrum methodologies to support sprint planning, backlog grooming, and release execution.
- Participate in feature demos, UAT coordination, and release readiness activities.
Modern SaaS Platform Exposure
- Gain hands-on experience with cloud-native, multi-tenant SaaS architectures, APIs, microservices, security, and scalability concepts.
- Support integration initiatives across CRM platforms (e.g., Salesforce), CPaaS providers, and enterprise ecosystems.
Customer & Stakeholder Engagement
- Join customer calls, usability sessions, and beta programs to capture feedback and validate product direction.
- Support preparation of product documentation, internal enablement, and launch materials.
What You Will Learn
- How enterprise CCaaS platforms are built and scaled.
- How AI is productized — from model capability to customer value.
- How to balance customer needs, technology constraints, and business strategy.
- How modern SaaS companies execute product management at scale.
Eligibility & Qualifications
- Bachelor’s degree in Engineering or Computer Science (or related technical discipline).
- Strong interest in Product Management, SaaS platforms, AI technologies, and cloud computing.
- Basic understanding of software development concepts, APIs, and web technologies.
- Familiarity with Agile development practices is a plus.
Desired Skills & Attributes
- Strong analytical and problem-solving mindset.
- Excellent communication and structured thinking skills.
- Curiosity about AI, data platforms, and digital customer experience technologies.
- Ability to work cross-functionally with engineering, design, and business teams.
- Entrepreneurial mindset with a bias for action and learning.
Career Path
This apprenticeship is designed to develop future Associate Product Owners , Associate Product Managers and Product Managers. High performers will have the opportunity to transition into a full-time product management role with increased ownership of product areas.
Why Join Us
- Work on a market-leading CCaaS platform from Five9 shaping the future of customer experience.
- Get early exposure to AI-first product development in a real enterprise environment.
- Structured mentorship from experienced product leaders.
- Opportunity to grow rapidly in one of the fastest-growing technology domains.
Five9 embraces diversity and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we are. Five9 is an equal opportunity employer.
View our privacy policy, including our privacy notice to California residents here: https://www.five9.com/pt-pt/legal.
Note: Five9 will never request that an applicant send money as a prerequisite for commencing employment with Five9.
Ready to apply?
Apply to Five9