Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

Summary:
Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities:

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 10+ years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Address:

Bangalore Office  

Tekion India Private Limited 

6th, 7th & 8th Floor, Helium, Bagmane Solarium City, Doddanekkundi Village, KR Puram Hobli, East Taluk, Bangalore - 560037 

Chennai Office

Embassy Splendid Zone, Block 2, 9th floor, Velan Nagar, Arulmurugan Nagar, Old Pallavaram, Chennai, Tamil Nadu 600043

Summary:

Leads advanced financial analysis and optimization strategies for cloud infrastructure, providing expert-level insight and technical guidance to drive cost efficiency, forecasting accuracy, and financial accountability across multi-cloud environments. This role partners closely with engineering, finance, and procurement teams to enable strategic cloud investment decisions.​

Duties & Responsibilities:

• ​ Lead in-depth cost modeling, forecasting, and trend analysis for AWS, Azure, GCP, and other cloud platforms.
• Design and implement scalable chargeback/showback models, allocation frameworks, and budget controls across business units.
• Serve as the primary expert on cloud cost optimization, including automation of rightsizing, usage analysis, and commitment planning (RI/SP/CUD).
• Collaborate with cloud engineering and architecture teams to ensure cost considerations are embedded in system design and scaling strategies.
• Provide financial oversight and scenario modeling to support large-scale cloud investments and vendor negotiations.
• Own and maintain FinOps dashboards, data pipelines, and cloud billing integrations with BI platforms.
• Define and drive FinOps best practices, governance standards, and cross-functional training initiatives.
• Mentor other analysts and serve as a lead contributor to FinOps maturity and tooling strategies.​

Job Complexity:

Leads the most complex, high-impact cloud financial analysis and optimization initiatives. Translates technical usage into strategic financial insights.

Required Supervision:

Operates independently with a high degree of autonomy. Trusted to guide FinOps execution and influence enterprise cloud strategy.

Expertise:

Deep subject matter expertise in cloud billing, cost modeling, and FinOps strategy. Recognized as a key influencer in cloud financial planning and optimization.​

Qualifications:

• ​ Bachelor’s or Master’s degree in Finance, Data Science, Engineering, or a related field.
• 7+ years of experience in cloud cost optimization, infrastructure finance, or enterprise technology operations.
• Advanced knowledge of public cloud platforms (AWS, Azure, GCP), billing constructs, and pricing strategies.
• Proficiency in SQL, Excel, and BI tools such as Tableau, Power BI, or Looker.
• Experience with cloud cost management platforms (e.g., Apptio Cloudability, CloudHealth, native tools).
• Strong technical acumen, communication skills, and ability to collaborate across engineering and finance.
• FinOps Certified Practitioner or Professional strongly preferred.

Summary:

Leads advanced financial analysis and optimization strategies for cloud infrastructure, providing expert-level insight and technical guidance to drive cost efficiency, forecasting accuracy, and financial accountability across multi-cloud environments. This role partners closely with engineering, finance, and procurement teams to enable strategic cloud investment decisions.​

Duties & Responsibilities:

• ​ Lead in-depth cost modeling, forecasting, and trend analysis for AWS, Azure, GCP, and other cloud platforms.
• Design and implement scalable chargeback/showback models, allocation frameworks, and budget controls across business units.
• Serve as the primary expert on cloud cost optimization, including automation of rightsizing, usage analysis, and commitment planning (RI/SP/CUD).
• Collaborate with cloud engineering and architecture teams to ensure cost considerations are embedded in system design and scaling strategies.
• Provide financial oversight and scenario modeling to support large-scale cloud investments and vendor negotiations.
• Own and maintain FinOps dashboards, data pipelines, and cloud billing integrations with BI platforms.
• Define and drive FinOps best practices, governance standards, and cross-functional training initiatives.
• Mentor other analysts and serve as a lead contributor to FinOps maturity and tooling strategies.​

Job Complexity:

Leads the most complex, high-impact cloud financial analysis and optimization initiatives. Translates technical usage into strategic financial insights.

Required Supervision:

Operates independently with a high degree of autonomy. Trusted to guide FinOps execution and influence enterprise cloud strategy.

Expertise:

Deep subject matter expertise in cloud billing, cost modeling, and FinOps strategy. Recognized as a key influencer in cloud financial planning and optimization.​

Qualifications:

• ​ Bachelor’s or Master’s degree in Finance, Data Science, Engineering, or a related field.
• 7+ years of experience in cloud cost optimization, infrastructure finance, or enterprise technology operations.
• Advanced knowledge of public cloud platforms (AWS, Azure, GCP), billing constructs, and pricing strategies.
• Proficiency in SQL, Excel, and BI tools such as Tableau, Power BI, or Looker.
• Experience with cloud cost management platforms (e.g., Apptio Cloudability, CloudHealth, native tools).
• Strong technical acumen, communication skills, and ability to collaborate across engineering and finance.
• FinOps Certified Practitioner or Professional strongly preferred.

As a Senior Database Engineer at Tekion, you will design, automate, and optimise database operations across our cloud-native automotive retail platform, connecting OEMs, dealerships, partners, and consumers. You’ll be working on scaling problems, laying down processes and streamlining requirements to actual executable tasks.

You’re expected to know in-depth about different storage and replication internals, trade-offs across SQL/NoSQL technologies, distributed systems fundamentals, transaction interaction and concurrency. A combination of this with strong Python fundamentals and Python scripting experience would make you a strong candidate for this role.

You should have at least 4+ years of experience. You should know about MongoDB in depth, and at least one SQL database like MySQL, MariaDB, PostgreSQL. People who want to build systems, not just manage them.

Key Responsibilities:

1. Core Database Engineering & Distributed Systems (Primary Focus):
1. Debug and prevent concurrency issues (deadlocks, lock escalation, starvation, long-running transactions) and advise teams on safe patterns (idempotency, retries, backoff, fencing tokens).
2. B-tree/LSM trade-offs, page layout, WiredTiger cache, journaling, WAL/redo/undo, checkpoints, compaction, MVCC behaviour
3. Backups (Logical vs Physical vs Snapshots based), upgradation of database systems and versions, data migration, and Disaster Recovery implementation
4. Query planner behaviour, statistics, cardinality estimation pitfalls
5. Indexing strategies and write amplification trade-offs
2. Reliability Engineering, Observability & Incident Response :
   Build and implement database reliability practices:

1. Lead incident response and postmortems; implement preventative controls and automated remediation.
2. Implement monitoring and alerting for replication lag, lock contention, buffer/cache health, slow query patterns, storage growth, and failover events.

1. Python Automation & Platform Tooling (Required):
   Develop and maintain robust Python tooling/services for:

• Automated health checks, failover verification, backup/restore validation, and consistency checks.
• Online schema change orchestration, safe rollout/rollback workflows, and guardrails in automation.
• Performance diagnostics automation (plan capture, workload fingerprinting).
• Build scalable automation that handles millions of records/events efficiently (attention to time/space complexity).

1. Data Modelling Across SQL & NoSQL:
   Guide data modelling decisions across relational and document/Key-Value stores:

• Normalisation vs denormalisation trade-offs
• Secondary index design, hot partition mitigation, and throughput planning
• TTL, archiving, and lifecycle policies
• Define governance for data correctness, durability, and operational safety in high-throughput systems

1. Collaboration, Standards & Enablement

1. Partner with application teams to design safe data access patterns, migration strategies, and operational standards.
2. Define best practices for production change management, access controls, auditing, and compliance requirements.
3. Mentor engineers and raise the bar on database engineering craftsmanship across the org.
4.  

Qualifications & Skills

Must have

• 4+ years of work experience as an engineer in a relevant role and responsibilities.
• Strong foundation in distributed systems and database fundamentals: CAP, consensus basics, replication, failure handling, and consistency.
• Deep understanding of transaction semantics, isolation levels, MVCC, locking, concurrency failure modes, storage engines and DB internals.
• Strong Python skills for building production-grade automation and diagnostics tooling.
• Hands-on experience operating and tuning production databases (MongoDB and at least one SQL system such as MySQL, PostgreSQL, MariaDB etc).
• Strong debugging and performance analysis skills; comfortable working from metrics, logs, traces, and low-level symptoms.
• Experience working with Linux and familiarity with common commands.

Nice to Have

• Experience with multi-region data architectures, global tables, and cross-region failover strategies.
• Familiarity with AWS and MongoDB Atlas.
• Understanding of Networking concepts like VPC, subnets, security groups, CIDR, peering etc.
• Experience with Kubernetes and/or self-managed database experience
• Experience building internal platforms (self-serve database ops, policy-as-code, safe migration frameworks).

What We’re Looking For

A senior engineer who:

• Thinks in trade-offs (latency vs consistency, durability vs throughput, cost vs performance), thinks deeply.
• Can reason from first principles about database behaviour under failure and load.
• Uses Python to operationalise best practices into repeatable, safe automation and can instruct others on best practices.
• Drives reliability, performance, and correctness across both SQL and NoSQL systems.
• Leads through technical clarity, ownership, and mentorship.

Job Description

We need a senior graphic designer who can think strategically and ship great work. You'll manage our brand's visual identity across all digital channels and work directly with the communication team, marketing, and leadership to create designs that connect with our audience. You'll mentor the design team, maintain quality standards, and help build the way we work. This role fits someone who wants to lead, create, and grow a design practice at a technology company that moves fast.

Key Responsibilities

Brand Vision & Consistency: You'll maintain our brand's visual standards and build the design systems that keep everything consistent. That means creating guidelines, components, and patterns that work across all platforms - so every project reinforces the brand without starting from scratch.

End-to-End Creative Leadership: You'll own design projects from start to finish across web, mobile, and marketing campaigns. That means taking concepts from initial ideas through final launch. You'll work with communications, marketing, product, and leadership to create designs that look sharp and move business metrics - whether that's revenue, adoption, or conversion.

Ideation & Storytelling: You'll research concepts and turn them into working designs. Then you'll present your work to different teams - product, marketing, leadership - and explain the thinking behind your JD - Associate Principle Graphic Designer 1 choices. That means showing why certain design decisions solve specific problems, not just what looks good. You need to make your case clearly whether you're talking to designers or marketers or executives. 

Team Leadership & Growth: You'll manage a small design team and help them grow. That means coaching designers on their projects, giving feedback that improves their work, and building accountability around quality. The goal is creating a design powerhouse where people own their craft and keep getting better at it. Holistic Design Oversight: You'll review all design work before it ships - product interfaces, illustrations, brand materials, presentations, and campaign visuals. That means maintaining quality standards across everything and making sure it all feels consistent. Nothing goes out without your approval.

Systems & Workflow Innovation: You'll build design systems and workflows that make the team more efficient. As we grow, you'll keep improving how we work - finding ways to move faster without dropping quality. The goal is scaling output while keeping the work sharp.

Strategic Design Advocacy: You'll represent design in leadership meetings and cross-functional discussions. That means explaining design decisions to executives and showing how they connect to business goals - whether that's Brand perception, revenue, adoption, or user retention. You'll need to make the case for design quality and user experience when priorities compete.

Qualifications

• Five or more years of hands-on visual and brand design experience in tech or SaaS, with a portfolio that shows clear thinking, strong storytelling, and high craft.
• A track record of leading or managing designers on real projects, with experience owning outcomes, not just visuals.
• Deep expertise in Figma and Adobe Creative Suite, plus comfort exploring new tools for motion, prototyping, and collaboration.
• Proven ability to build and evolve brand identities, logos, and web experiences that can scale across enterprise audiences and channels. 
• Strong communication skills with real executive presence: you can defend your work with clarity, invite feedback, and align teams around a shared vision.
• Experience running projects end to end, from brief and discovery through delivery, with a structured approach to planning, prioritizing, and followthrough.
• A habit of staying ahead of design, product, and culture trends, and turning that curiosity into concrete ideas we can ship.
• High personal accountability: you take ownership, push for better outcomes, and hold yourself and others to a strong quality bar.
• Genuine passion for design and storytelling, and a desire to grow a small team into a tight, proud, high-performing creative group. 

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

ROLE SUMMARY: The Senior Financial Analyst leads complex financial analyses and planning activities to support strategic decision-making and business performance management. This role partners with cross-functional teams to provide financial insights, manage forecasting processes, and improve reporting capabilities across the organization.

KEY RESPONSIBILITIES

Financial Planning & Analysis:

• Lead budgeting, forecasting, and long-range planning activities for assigned departments or business units.
• Develop advanced financial models to analyze business scenarios, track performance, and support strategic initiatives.
• Perform variance analysis and partner with business leaders to identify risks, opportunities, and efficiency improvements.

Reporting & Insights

• Prepare and deliver financial reporting packages and dashboards for leadership, highlighting key trends and insights.
• Support business units with KPI reporting on key operational, sales, and financial metrics.
• Provide ad-hoc reporting and forward-looking analysis, proactively engaging business leaders in gap analysis and course correction.

Close & Compliance

• Support monthly and quarterly close processes, including accruals, reconciliations, and financial statement analysis.
• Apply a thorough understanding of US GAAP for purposes of financial statement analysis.

Process Improvement & Systems

• Contribute to process improvements, financial systems upgrades, and automation initiatives.
• Identify and assist in the implementation of enhancements to financial reporting and planning systems.

QUALIFICATIONS

Required

• 5-6yrs years of experience in FP&A, financial analysis, or corporate finance.
• Bachelor's degree in Finance, Accounting, Economics, or a related field.
• Proficient in financial modeling, Excel, and reporting tools (e.g., Power BI, Anaplan, Adaptive Insights).
• Experience with ERP systems (e.g., Oracle, SAP, NetSuite) and financial planning platforms.
• Thorough understanding of US GAAP for financial statement analysis.
• Excellent communication, problem-solving, and cross-functional collaboration skills.
• Proven ability to manage competing deadlines and shifting priorities with minimal supervision.

Preferred

• MBA or CFA designation.
• Experience in a high-growth or publicly traded company environment.
• Familiarity with data visualization and BI tools.

CORE COMPETENCIES

Candidates will be evaluated against the following behavioral competencies:

Role Summary

Tekion is seeking a Director, GTM Product Management to lead and scale our Go-To-Market engine from Bangalore, India. This is a hybrid leadership role that spans product marketing, product strategy, GTM engineering, AI-powered content operations, and competitive enablement — reporting to the VP of Product Innovation and Design or VP of Product Marketing. You will own the strategy, systems, and content infrastructure that connects Tekion’s product innovation to revenue outcomes, building AI-native workflows that accelerate pipeline generation, shorten sales cycles, and increase competitive win rates across our Automotive Retail Cloud (ARC), Automotive Enterprise Cloud (AEC), and Automotive Partner Cloud (APC) product lines. You will also play a critical role in shaping product strategy by translating market intelligence, competitive dynamics, and customer insights into strategic inputs that influence the product roadmap and investment priorities.

Roles and Responsibilities

• Go-To-Market Strategy & Execution — Own end-to-end GTM planning for new product launches and feature releases across ARC, AEC, and APC — from Ideal Customer Profile (ICP) definition (including target dealer groups by size, geography, OEM affiliation, and technology maturity) and channel strategy through pricing alignment, partner co-marketing, and launch execution.

• AI-Powered Content Pipeline Design — Architect and operate automated content systems that transform raw inputs (call transcripts, win/loss data, competitor signals, CRM data) into publish-ready sales assets including battle cards, objection handlers, one-pagers, value propositions, ROI calculators, value/ROI justification content, and pre-call briefings.

• Prompt Engineering & Agent Prototyping — Design, test, and optimize prompt libraries and AI agent workflows for GTM use cases such as competitive intelligence extraction, personalized outbound sequencing, dynamic battle card generation, and real-time objection handling support during sales calls.

• Competitive Intelligence Program — Build and maintain a continuous competitive monitoring system that tracks competitor pricing, features, messaging, customer reviews, and analyst coverage — translating insights into actionable sales tools within hours, not weeks. Ensure the competitive enablement program scales through automation rather than manual effort.

• Sales Enablement & Revenue Tooling — Create and manage the content arsenal that sales uses in-deal: pitch decks, demo scripts, talk tracks, persona-specific email templates, and competitive positioning guides. Partner with Product Marketing teams to align enablement materials with broader campaign themes and product narratives. Ensure assets are delivered inside the tools reps already use (CRM, email, meeting prep) rather than buried in a wiki.

• GTM Workflow Automation — Design and deploy multi-step automated workflows connecting Tekion’s CRM, marketing automation, enrichment tools, and analytics into a unified revenue engine — including sales trigger systems that react to buying signals (funding rounds, leadership changes, DMS contract expirations) with immediate, tailored follow-ups.

• Win/Loss Analysis & Market Intelligence — Run structured win/loss programs, buyer persona research, and voice-of-customer analysis. Extract patterns from deal data and call transcripts to continuously sharpen positioning, enablement content, and product feedback loops.

• Content-to-Revenue Attribution — Implement measurement frameworks that track which enablement assets and GTM programs actually influence win rates, deal velocity, and revenue — not just views and downloads. Use data to prioritize investment and retire underperforming content.

• Product Strategy & Roadmap Influence — Translate market intelligence, competitive analysis, win/loss patterns, and voice-of-customer insights into strategic recommendations that shape Tekion’s product roadmap and investment priorities. Serve as a bridge between GTM and Product/Engineering, ensuring that market reality informs build decisions.

• Team Leadership — Build, mentor, and scale a high-performing GTM product management team in Bangalore. Set the vision, operating cadence, and quality bar for all GTM outputs. Partner closely with Product, Engineering, Sales, Solutions, and Customer Success leadership across time zones.

Qualifications and Education Requirements

• At least 10 years of experience in product management/marketing, product strategy, sales enablement, or revenue operations within B2B SaaS

• Demonstrated experience building and operating AI-powered content pipelines, prompt engineering workflows, or AI agent prototypes for GTM functions. Hands-on comfort with LLMs, automation platforms, and structured prompt design is required — not theoretical knowledge.

• Exceptional written and verbal communication skills with the ability to translate complex technical capabilities into compelling, persona-specific narratives for diverse audiences (dealers, OEM executives, technology partners, end consumers).

• Strong analytical mindset with experience in content-to-revenue attribution, win/loss analysis, and data-driven GTM optimization.

• Experience influencing product strategy and roadmap priorities through structured market intelligence, competitive analysis, and customer insights.

• Experience leading and scaling distributed teams across geographies and time zones, with a bias toward building systems and playbooks that scale beyond individual effort.

• Bachelor’s degree in Product, Business, Marketing, Engineering, or a related field. MBA or advanced degree is a strong plus.

Preferred Skills

• Automotive or DMS software product expertise

• Experience building competitive intelligence programs that measurably improved win rates in enterprise sales cycles.

• Strong technical fluency with GTM tooling ecosystems including CRM platforms (Salesforce, HubSpot), marketing automation, project management tools (Jira, Confluence), and data enrichment platforms.

• Experience designing and deploying automated outbound and sales trigger workflows that connect multiple systems into cohesive revenue pipelines.

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact. 

Why this Role Matters 

• Accelerate the rollout of LLM-powered and agent-driven features across Tekion products. 

• Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders. 

• Operationalize secure, compliant, and explainable LLM and agentic services at scale. 

• Convert Applied Sciences models into scalable, compliant, cost‑efficient production services. 

• Standardize how models are trained, validated, deployed, and monitored across Tekion products. 

• Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference. 

What You’ll Do 

• Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts. 

• Integrate with the LLM Gateway/MCP, prompt/config versioning. 

• Build and orchestrate CI/CD pipelines. 

• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality. 

• Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems. 

• Monitor, detect, and mitigate risks unique to LLMs and agentic systems. 

• Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics. 

• Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph. 

• Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets. 

• Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage. 

• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking. 

• Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation. 

• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path. 

Desired Skills and Experience 

• 6+ years in ML engineering/MLOps or backend/platform engineering with production ML. 

• Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores. 

• Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing. 

• Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.). 

• Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns. 

• Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices. 

• Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering. 

• Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection. 

• Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots. 

• Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience. 

• Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability. 

Preferred Mindset 

• Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics. 
• Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs. 
• Systems thinker: You design for multi-tenant scale, portability, and cost efficiency
• Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach. 

Senior Software Engineer  -  Senior Machine Learning Platform

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 5 - 7 years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

At Tekion, we’re building the only cloud -native platform that is transforming the automotive retail industry, leap frogging it into the future and providing unparalleled customer experience. We’re creating seamlessly integrated, elegant, and intuitive solutions built with cutting edge technology and powered by Big Data, Machine Learning (ML)/ AI and Internet of Things (Connected vehicle to connected devices). We’re harnessing passion, entrepreneurial spirit, deep industry expertise and the latest technologies to create something very special. We’re inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it!

Core Responsibilities:
• Taking ownership of customer issues reported and seeing problems through to resolution
• Researching, diagnosing, troubleshooting, and identifying solutions to resolve system issues
• Following standard procedures for proper escalation of unresolved issues to the appropriate internal teams
• Ability to understand the application both functionally and technically
• Ref er to internal database or external resources to provide accurate tech solutions
• Ensure all issues are properly logged
• Prioritize and manage several open issues at one time
• Prepare accurate and timely reports
• Document technical knowledge in the form of notes and manuals

Required Skills:
• Experience as an Application/Product/Customer Support Engineer.
• Ability to learn and master employer-specific software
• Complex problem solving
• Written and verbal communication skills
• Ability to diagnose & address application issues
• Basic understanding of IoT and software - preferred not mandatory
• Candidate should be ready for rotational shift perks and benefits

Hands on experience on chats / Ticketing tools

Role Overview

As the Manager, Database Reliability Engineering (DBRE), you will lead a team of expert DBREs responsible for the health, performance, automation, and scalability of Tekion’s data backbone. Your focus will be on operational excellence, automation first, and continuous improvement of reliability and efficiency for our MongoDB, MySQL, and Elasticsearch clusters. You'll mentor your team, drive innovation in database automation (using Go or Python), and collaborate with product, engineering, and Cloud teams.

Key Responsibilities

• Team Leadership & Strategy: Build, mentor, and lead a high-performing Database Reliability Engineering team, fostering a culture of technical excellence, ownership, and collaboration.
• Database Operations & Reliability: Oversee the reliability, performance, availability, and scalability of MongoDB, MySQL, and Elasticsearch across multiple environments and regions.
• Automation & Engineering: Architect and drive automation for database provisioning, scaling, backups, upgrades, patching, and recovery using Go or Python. Establish standards for Infrastructure as Code and self-service database management.
• Monitoring & Incident Response: Implement and enhance automated monitoring, alerting, performance tuning, and self-healing solutions. Lead major incident response, postmortems, and continuous improvement.
• Collaboration: Partner with SRE, CloudOps, Security, and development teams to understand requirements, drive database reliability improvements, and support feature launches.
• Best Practices & Documentation: Define and enforce database reliability best practices, documentation, runbooks, and automation guides. Promote DBRE standards and knowledge sharing.
• Capacity & Cost Management: Monitor capacity, forecast growth, and work with engineering and product teams on cost-effective database scaling.
• Security & Compliance: Ensure security, compliance, and data protection in all database operations and automation solutions.

Required Qualifications

• Bachelor's or master’s in computer science, Engineering, or equivalent practical experience.
• 8+ years of experience in database engineering, DBRE, or SRE roles, with at least 3+ years in a technical/team leadership or management position.
• Deep hands-on experience managing and automating MongoDB, MySQL, and Elasticsearch (good to have).
• Strong programming skills in Go or Python for database automation and tooling.
• Proven ability to design and implement automation for database lifecycle operations, monitoring, and self-healing.
• Expertise in building, running, and scaling highly available database clusters (replication, sharding, backup/restore, performance tuning).
• Strong knowledge of database security, access controls, patching, and compliance practices.
• Excellent communication, incident leadership, and cross-functional collaboration skills.
• Track record of hiring, mentoring, and developing technical talent.
• Prior Manager experience is a must 

About Tekion 

Tekion is revolutionizing the automotive landscape through cloud-native platforms and intelligent products that power dealerships, OEMs, and partners worldwide. At Tekion, we’re passionate about building a future where technology simplifies, secures, and transforms the way vehicles are bought, sold, and serviced. Our collaborative and innovation-driven culture is fueled by a relentless commitment to security, reliability, and scalability as we accelerate our global footprint. 

Team Overview 

You will lead a high-impact Cloud Infrastructure Automation & SRE team within Cloud Engineering, focusing on building and operating secure, reliable, scalable, resilient & self-serve infrastructure platforms for all Tekion. In close partnership with our Cloud Security, Product Security, and Application teams, you’ll play a vital role in establishing and enforcing security best practices and automation-first principles across all layers of our cloud environments. 

Roles and Responsibilities 

Strategic Leadership: Lead and grow a team of talented cloud infrastructure engineers and SREs, providing technical and people leadership, mentorship, and career development. 

Infrastructure as Code: Drive the adoption and evolution of infrastructure automation (IaC) frameworks (such as Terraform, Pulumi, CRD) to enable consistent, auditable, and scalable platform management. 

Operational Excellence: Oversee the reliability, scalability, and performance of critical infrastructure services, ensuring high availability, rapid mitigation of incidents, and root cause analysis. 

Platform Enablement: Architect, build, and optimize cloud platforms (AWS/GCP/Azure), Kubernetes clusters, and CI/CD pipelines to support the needs of Tekion’s products and services. 

Security & Compliance: Partner with Cloud Security and Product Security teams to define, implement, and maintain robust security controls, policies, and monitoring across infrastructure and applications. 

Collaboration: Work cross-functionally with engineering, security, and application teams to balance operational needs, reliability, and security requirements in cloud environments. 

Incident Management: Establish, refine, and lead SRE practices for monitoring, alerting, on-call processes, incident response, and postmortems with a security-first approach. 

Automation & Tooling: Identify opportunities for automation across infrastructure, operations, and security workflows; enable self-service tooling and guardrails for developers. 

Continuous Improvement: Promote a culture of continuous learning, process optimization, and operational excellence, keeping up to date with emerging security and cloud technologies. 

Reporting & Metrics: Track and present key performance indicators (SLAs, SLOs, security posture, automation coverage, incident metrics) to stakeholders and executive leadership. 

What makes you relevant for this role? 

• Bachelor’s or master’s degree in computer science, Engineering, or related field OR equivalent practical experience. 

• 10+ years of experience in DevOps, Site Reliability Engineering, or Cloud Infrastructure roles, with at least 2+ years in technical leadership or management. 

• Hands-on expertise in cloud platforms (AWS/GCP/Azure), containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, CloudFormation, Ansible, etc.). 

• Deep knowledge of cloud security best practices, cloud-native IAM, network security, secrets management, and compliance (SOC2, ISO 27001, etc.). 

• Proven experience driving operational reliability with SRE methodologies: monitoring, alerting, incident response, and post-incident analysis. 

• Track record of building and developing high-performing infrastructure or SRE teams. 

• Strong background in automation, CI/CD pipeline management, and system architecture at scale. 

• Excellent communication, stakeholder management, and cross-functional collaboration skills. 

• Security Integration: Embed security best practices across the software development lifecycle (SDLC), from code commit to deployment, ensuring "security by design."
• Collaboration: Work closely with Cloud Security and Product Security teams to develop and enforce security standards, policies, and frameworks.
• Infrastructure Hardening: Implement and automate security controls across AWS/Azure/GCP resources, Kubernetes clusters, containers, and other infrastructure components.
• CI/CD Security: Integrate automated security testing, static and dynamic analysis, and vulnerability scanning into CI/CD pipelines.
• Threat Detection & Incident Response: Develop and maintain monitoring/alerting for security incidents; participate in incident triage, root cause analysis, and response efforts.
• Tooling & Automation: Build and maintain automation for compliance checks, secrets management, access controls, patching, and audit logging.
• Governance: Ensure the team’s infrastructure and deployments are compliant with industry regulations and Tekion’s internal security requirements.
• Continuous Improvement: Stay current with emerging threats, vulnerabilities, and security best practices; propose and implement relevant improvements.
• Evangelism: Foster a security-first mindset within DevOps and engineering teams through knowledge sharing, documentation, and training.

• Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent practical experience.
• 3-7 years of experience in DevOps, Site Reliability Engineering, or Security Engineering roles.
• Solid hands-on experience with cloud infrastructure (AWS/GCP/Azure).
• Deep understanding of secure infrastructure design, identity and access management, network security, and related best practices.
• Experience securing container platforms (Docker, Kubernetes) and modern CI/CD toolchains (e.g., Jenkin, Tekton, GitHub actions, ArgoCD).
• Proficiency in at least one scripting/programming language (Python, Go, etc.) and strong automation skills.
• Practical familiarity with vulnerability management, scanning, threat modeling, and remediation workflows.
• Strong collaboration, communication, and documentation abilities.

• Opportunity to work with some of the smartest minds to solve complex security challenges at scale.
• Impactful role in shaping and securing a global, cloud-native & AI driven platform.
• Innovative, collaborative, and fast-paced culture.

Summary:

The Senior Manager, DevOps leads the strategic direction and execution of Tekion’s DevOps and infrastructure automation initiatives. This role oversees global teams responsible for platform reliability, CI/CD, observability, and cloud operations. It focuses on scaling infrastructure, improving deployment velocity, and ensuring operational excellence across the engineering organization.

Duties & Responsibilities:

• Defines and executes the DevOps roadmap, aligning automation, reliability, and scalability goals with organizational priorities.
• Manages and scales teams responsible for cloud infrastructure, CI/CD pipelines, monitoring, and SRE practices.
• Partners with Engineering, Product, and Security leadership to align on architectural standards and operational policies.
• Leads modernization initiatives including infrastructure as code, containerization, and service mesh adoption.
• Establishes SLAs, incident response processes, and performance metrics for platform health and resilience.
• Oversees budget planning, vendor evaluation, and tooling strategy to ensure efficiency and scalability.
• Mentors DevOps managers and senior engineers, fostering a culture of accountability, innovation, and continuous improvement.

Job Complexity:

Leads global, cross-functional infrastructure programs with high strategic value. Balances short-term platform demands with long-term architectural and operational vision.

Required Supervision:

Operates with complete autonomy. Responsible for team leadership, budget oversight, and cross-department alignment with executive stakeholders.

Expertise:

Demonstrates deep expertise in DevOps, infrastructure automation, cloud architecture, and site reliability engineering. Influences enterprise-wide technical decisions and leads transformation across engineering operations.

Qualifications:

• 10+ years of experience in DevOps, cloud engineering, or infrastructure leadership roles
• 5+ years in technical leadership or management, including global team oversight
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• Strong expertise in AWS, GCP, or Azure and infrastructure-as-code tools like Terraform, CloudFormation, or Pulumi
• Proficiency in CI/CD pipeline tooling (e.g., Jenkins, GitLab CI/CD, ArgoCD) and observability stacks (e.g., Prometheus, Grafana, ELK)
• Experience implementing SRE practices, reliability metrics, and service-level objectives
• Excellent leadership, strategic thinking, and cross-functional collaboration skills

Job Description-

Key Responsibilities-

At Tekion, we’re building the only cloud -native platform that is transforming the automotive retail industry, leap frogging it into the future and providing unparalleled customer experience. We’re creating seamlessly integrated, elegant, and intuitive solutions built with cutting edge technology and powered by Big Data, Machine Learning (ML)/ AI and Internet of Things (Connected vehicle to connected devices). We’re harnessing passion, entrepreneurial spirit, deep industry expertise and the latest technologies to create something very special. We’re inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it!

Core Responsibilities:
• Taking ownership of customer issues reported and seeing problems through to resolution
• Researching, diagnosing, troubleshooting, and identifying solutions to resolve system issues
• Following standard procedures for proper escalation of unresolved issues to the appropriate internal teams
• Ability to understand the application both functionally and technically
• Ref er to internal database or external resources to provide accurate tech solutions
• Ensure all issues are properly logged
• Prioritize and manage several open issues at one time
• Prepare accurate and timely reports
• Document technical knowledge in the form of notes and manuals

Required Skills:
• Experience as an Application/Product/Customer Support Engineer.
• Ability to learn and master employer-specific software
• Complex problem solving
• Written and verbal communication skills
• Ability to diagnose & address application issues
• Basic understanding of IoT and software - preferred not mandatory
• Candidate should be ready for rotational shift perks and benefits

Hands on experience on chats / Ticketing tools

Tekion seeks an exceptionally talented and seasoned Staff / Lead Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale.  
 
Key Responsibilities 

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges. 

• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions. 

• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives. 

• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services. 

• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation. 

• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth. 

• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership. 

• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI 

Core Competencies & Technical Expertise 

            The successful candidate will demonstrate mastery in the following areas: 

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI. 

• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data. 
   
   

Deep Learning: 

• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch. 

• Extensive experience implementing advanced neural network architectures. 

• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g.,spaCy) methodologies. 

• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications. 

Technical Proficiencies: 

• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous. 

• Proficiency with cloud computing platforms (GCP, Azure, AWS). 

• Expertise in experimental design (A/B testing, causal inference). 

• Proficient in version control systems (Git). 

Required Qualifications 

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field. 

• A minimum of 7 - 9 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value. 

• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach. 

• Proven experience in programming, data manipulation, and building models in a business context. 

• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences. 
   

Ideal Candidate Profile 
 

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving. 

• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable. 

• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred. 

• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences. 

• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams. 

• A commitment to continuous personal and team development within a collaborative, high-performance culture. 

Perks and Benefits

• Competitive compensation 

• Generous stock options 

• Medical Insurance coverage 

• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies 

Why This Role Matters
We're looking for a Data Platform Engineer with deep systems engineering expertise and a passion for building reusable infrastructure. You'll help
architect and deliver the internal frameworks that power data ingestion, transformation, observability, and self-serve analytics across the company. Your work will be central to enabling scalable, multi-tenant ingestion pipelines (including CDC via Debezium), serving layers built on Trino, and robust tooling that lets teams move fast without compromising on data quality or platform
health.

What Makes This Opportunity Unique
Build platform tooling for multi-region, multi-tenant data infrastructure using modern open-source and cloud-native technologies.
Lead engineering efforts around CDC pipelines using Debezium, enabling reliable change capture from application databases.
Shape the developer experience for data engineers, from ingestion to publishing and consumption, with metadata-aware automation.
Drive the evolution of data serving infrastructure using Trino and open table formats like Delta Lake or Iceberg.
Work at the intersection of data engineering, infrastructure, and platform strategy, directly influencing core architectural decisions.

Responsibilities

• Design and implement foundational frameworks for ingestion, orchestration, schema validation, and metadata management.
• Build robust, scalable pipelines for Change Data Capture (CDC) using Debezium integrated with Kafka and Spark.
• Develop internal tooling to standardize and accelerate data ingestion, transformation, and publishing workflows.
• Optimize data serving layers powered by Trino, including metadata syncing, security filtering, and performance tuning.
• Partner with SRE and Infra teams to build autoscaling, self-healing, and cost-optimized Spark jobs on AWS EMR.
• Implement observability features — logs, metrics, alerts — for critical platform services and data pipelines.
• Define and enforce standards for schema evolution, lineage tracking, and data governance.
• Automate platform operations using CI/CD pipelines, metadata-driven configurations, and infrastructure-as-code.

Desired Skills & Experience

• 7+–12 years of experience in data platform, infrastructure, or backend systems engineering roles.
• Strong systems engineering fundamentals — distributed systems, fault tolerance, performance tuning.
• Expertise in Apache Spark with production experience on AWS EMR.
• Experience building or managing CDC pipelines using tools like Debezium, Kafka Connect, or custom connectors. Familiarity with streaming systems such as Kafka, Kinesis, or Flink.
• Experience serving data using Trino or Presto in a multi-tenant environment.
• Proficiency in Python, Java or Scala, and Unix/Linux systems.
• Strong understanding of open table formats like Delta Lake or Apache Iceberg.
• Exposure to infrastructure as code (Terraform, CloudFormation) and CI/CD automation.

Preferred Mindset

• Platform-first thinker — designs systems for scale, abstraction, and reusability.
• Builder's bias — values automation, clean interfaces, and measurable SLAs.Deep collaborator — partners well across Data, Infra, and Engineering teams.
• Operational discipline — understands the impact of monitoring, logging,and reliability.

Why This Role Matters
We're looking for a Data Platform Engineer with deep systems engineering expertise and a passion for building reusable infrastructure. You'll help
architect and deliver the internal frameworks that power data ingestion, transformation, observability, and self-serve analytics across the company. Your work will be central to enabling scalable, multi-tenant ingestion pipelines (including CDC via Debezium), serving layers built on Trino, and robust tooling that lets teams move fast without compromising on data quality or platform
health.

What Makes This Opportunity Unique
Build platform tooling for multi-region, multi-tenant data infrastructure using modern open-source and cloud-native technologies.
Lead engineering efforts around CDC pipelines using Debezium, enabling reliable change capture from application databases.
Shape the developer experience for data engineers, from ingestion to publishing and consumption, with metadata-aware automation.
Drive the evolution of data serving infrastructure using Trino and open table formats like Delta Lake or Iceberg.
Work at the intersection of data engineering, infrastructure, and platform strategy, directly influencing core architectural decisions.

Responsibilities

• Design and implement foundational frameworks for ingestion, orchestration, schema validation, and metadata management.
• Build robust, scalable pipelines for Change Data Capture (CDC) using Debezium integrated with Kafka and Spark.
• Optimize data serving layers powered by Trino, including metadata syncing, security filtering, and performance tuning.
• Partner with SRE and Infra teams to build autoscaling, self-healing, and cost-optimized Spark jobs on AWS EMR.
• Implement observability features — logs, metrics, alerts — for critical platform services and data pipelines.
• Define and enforce standards for schema evolution, lineage tracking, and data governance.
• Automate platform operations using CI/CD pipelines, metadata-driven configurations, and infrastructure-as-code.

Desired Skills & Experience

• 5-7 years of experience in data platform, infrastructure, or backend systems engineering roles.
• Strong systems engineering fundamentals — distributed systems, fault tolerance, performance tuning.
• Expertise in Apache Spark with production experience on AWS EMR.
• Experience building or managing CDC pipelines using tools like Debezium, Kafka Connect, or custom connectors. Familiarity with streaming systems such as Kafka, Kinesis, or Flink.
• Experience serving data using Trino or Presto in a multi-tenant environment.
• Proficiency in Python, Java or Scala, and Unix/Linux systems.
• Strong understanding of open table formats like Delta Lake or Apache Iceberg.
• Exposure to infrastructure as code (Terraform, CloudFormation) and CI/CD automation.

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

Desired Skills & Experience 

• 4 - 5+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 5+ - 8+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

Job Summary - Software Platform Architect

The Software Platform Architect is responsible for the high-level design, development, and evolution of scalable software platforms that support multiple products and business needs. This role collaborates with cross-functional teams—including engineering, product, and operations—to define technology standards, guide architectural decisions, and ensure the platform’s reliability, scalability, and security.

Key Responsibilities

• Lead the architecture and design of Integration and System Integrator Platform platforms, ensuring alignment with business objectives and technical strategy.
• Define and promote the use of architectural patterns, best practices, and standards across the engineering organization.
• Collaborate with development teams to translate business requirements into robust, scalable, and modular solutions.
• Evaluate and select appropriate technologies, frameworks, and tools to meet platform needs.
• Oversee integration with internal and third-party systems, ensuring data integrity and optimal performance.
• Conduct architecture reviews and provide technical guidance to engineering teams throughout the software development lifecycle.
• Identify and address potential bottlenecks, vulnerabilities, and system failures.
• Maintain documentation of architecture, processes, and best practices.
• Stay current with emerging technologies and industry trends, evaluating their potential impact on the platform.
• Mentor and coach engineering teams on architectural principles and practices.

Qualifications

• Bachelor’s or master's degree in computer science, Software Engineering, or related field.
• Experience in building at event driven applications at scale
• 10+ years of relevant experience in software development and architecture, with a focus on building platforms or large-scale systems.
• Experience is large scale messaging systems like Kafka
• Experience using Mongodb, ElasticSearch, MySQL, Postgresql
• Proven experience in building platform components using the java, SpringBoot.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and container orchestration (e.g., Kubernetes, Docker).
• Strong knowledge of APIs, microservices, data storage, and integration methodologies.
• Experience in SaaS platform architecture or development.
• Familiarity with DevOps practices and CI/CD pipelines.
• Experience with security, compliance, and regulatory requirements for enterprise software.
• Excellent problem-solving, communication, and leadership skills.
• Experience working in Agile environments.
• Experience in using AI tools (Augment, Cursor, Claude code)

Job Summary - Software Architect(Frontend)

The Software Architect – Frontend is responsible for leading the design, architecture, and implementation of modern, scalable, and maintainable frontend applications across our product suite. This role collaborates cross-functionally with designers, backend engineers, and product managers to ensure a seamless and consistent user experience, driving the adoption of best practices in frontend engineering and staying abreast of the latest technology trends.

Key Responsibilities:

· Define, design, and document the architecture for frontend applications, ensuring scalability, performance, accessibility, and maintainability.

· Establish and enforce the use of frontend development best practices, frameworks, and design patterns across teams.

· Collaborate closely with UX/UI designers to translate design concepts into functional, pixel-perfect user interfaces.

· Work with backend engineers to design and implement robust APIs and data integration strategies.

· Provide technical guidance and mentorship to frontend development teams, conducting code reviews and promoting a culture of continuous improvement.

· Optimize frontend performance for various browsers and devices, proactively identifying bottlenecks and areas for improvement.

· Evaluate and select technologies, frameworks, and tools to support the evolving needs of the frontend platform.

· Contribute to cross-team architectural initiatives and promote reusability across web and mobile solutions.

· Stay up to date with emerging trends in frontend development, evaluating their relevance and potential impact.

· Maintain thorough documentation of frontend architecture, workflows, and best practices.

Qualifications

· Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

· 8+ years of professional frontend development experience, including significant experience in architectural or lead roles.

· Expertise in JavaScript, TypeScript, HTML5, CSS3, and modern frontend frameworks (e.g., React, Angular, Vue.js).

· Experience architecting and building large-scale, high-performance web applications.

· Strong understanding of web performance, security, accessibility standards (e.g., WCAG), and responsive design principles.

· Proven experience with state management solutions, component-based architecture, and modular design.

· Familiarity with backend integration, RESTful APIs, and micro frontends.

· Proficiency in build tools (e.g., Webpack, Babel), testing frameworks, and CI/CD pipelines.

· Excellent communication, leadership, and problem-solving abilities.

· Experience working in Agile or cross-functional teams.

· Experience with mobile web or hybrid app development.

· Knowledge of UI/UX best practices and collaboration with design systems teams.

· Contributions to open-source frontend projects or active involvement in frontend technology communities.

· Experience with internationalization, localization, and accessibility compliance in web applications.

· Experience in using AI tools (Augment, Cursor, Claude Code)

Job Description

At Tekion, Design and user experience are at the forefront of everything we do. Our design teams include designers, researchers, content strategists, and engineers who are passionate about quality, usability, and simplicity. We work together to collaboratively to solve complex challenges and craft experiences that highlight our products' unique capabilities. Tekion’s 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, Europe and we’re growing. 

As a Senior Product Designer, you'll tackle complex problems and transform them into intuitive, accessible and easy-to-use designs — from the first-time user to the sophisticated expert. Achieving this goal requires collaboration with teams of Designers, Researchers, Engineers and Product Managers throughout the design process—from creating user flows and wireframes to building user interface mock-ups and prototypes. At each stage, you will anticipate what our users need, advocate for them and ensure that the final product is easy to use and solving their problems.

What you bring to the team 

• User Advocacy: Champion the users throughout the design process and prioritize their needs throughout the product development cycle. You are someone who balances user needs with platform constraints while solving complex problems. 
• Inspire with Innovation: Brainstorm and conceptualise solutions that set new industry standards and deliver seamless, high-quality end-to-end experiences. You will be a part of a fast-paced team that works across other departments to create inclusive solutions. 
• Cross Functional Collaboration: You have a proven ability to work closely with product managers, engineers, marketers, and other stakeholders translating product requirements into functional, user-friendly designs. Being a part of a cross functional team, you are someone who can leverage collaboration methodologies like design workshops and thrive in fast-paced environments to build quality designs that benefits the user. 
• Investigator: You question assumptions and clarify requirements throughout the design process. You are a keen observer of user behaviour and can reframe problems to uncover innovative solution spaces while collaborating with your peers. You can think on your feet and come up with realistic trade-offs as the situation requires.

Skills and Qualifications 

• Systems Thinking: As a Senior, you understand how certain design components interact within a larger ecosystem and therefore can gauge the ripple effects of a design decision across a platform. You can design scalable and reusable solutions that work across multiple products and teams. 
• Figma Magician: Using Figma is like second nature to you — you breathe autolayouts, frames and responsive design. You have strong proficiency in both UX and visual design, with a demonstrated ability to deliver high quality and organised designs. Expertise in secondary tools like Framer, Principle, Miro, etc is a plus. You have impeccable understanding of various design systems, their components, variables, tokens, and can leverage best practices to your advantage when ideating. But you are courageous enough to break out of the mould when needed. 
• Storyteller: Create compelling narratives around design decisions and articulate thinking and solution rationale effectively. Present ideas and strategies clearly to team members and stakeholders, gather feedback before incorporating them in the designs. Build rapport with teams that depend on platform components. 

The Essentials

• You bring 5+ years' experience in end-to-end product design, with a robust portfolio showcasing user-centred design solutions that have delivered tangible results. You have an eye for detail, curiosity and growth mindset driving you as a designer. 
• Bachelor's degree in computer science, Human-Computer Interaction (HCI), Design, or equivalent practical experience. 
• Experience in designing for B2B, enterprise, or platform applications is highly desirable, but isn’t strictly necessary. 
• Strong proficiency in both UX and visual design, with a demonstrated ability to deliver high-quality designs that meet user needs and business objectives. 

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful Companies

Role Overview

This is an individual contributor role requiring strong product instincts, technical fluency, and the ability to operate autonomously across the full delivery lifecycle. The ideal candidate is equally comfortable in a whiteboard session defining a solution and in a sprint review tracking execution details Expectations Own the intake, prioritization, and end-to-end product delivery of AEC platform requirements driven by OEM program teams. This role works closely with AEC platform product and engineering stakeholders to ensure solutions are scalable and reusable, while partnering with program teams to translate OEM needs into clear requirements and execution-ready work items.

Key Responsibilities

· Consolidate and prioritize platform asks across OEM programs with program leadership; manage tradeoffs and release scope

· Define solutions and author high-quality PRDs covering scope, workflows, data contracts, acceptance criteria, and rollout; create and manage epics and stories in the tracking system

· Drive cross-team solution alignment; identify dependencies early and secure commitments

· Lead grooming with engineering, QA, and TPMs to obtain estimates, sequencing, and risk/dependency tracking; ensure release readiness

· Track execution through release, escalate blockers, and maintain clear stakeholder communication

· Post-release: monitor outcomes, triage issues versus enhancements, and feed learnings back into the roadmap

Ideal Candidate

 Must-haves: 5+ years in enterprise SaaS PM, strong PRD writing skills, executive stakeholder management, platform architecture fluency, and experience leading engineering grooming independently.

Strong plus: Automotive retail or DMS experience, familiarity with OEM-dealer dynamics, exposure to Tekion AEC or comparable platforms. 

Key Hire Signal
This person must be able to design solutions and write PRDs that survive expert review without needing platform PMs in the room. If they rely on collaborative grooming to refine requirements, they will create bottlenecks in the delivery cycle. 

Perks and Benefits

• Competitive compensation

• Generous stock options

• Medical Insurance coverage

• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

We are looking for a Senior NetSuite Developer to design, build, and enhance solutions within our ERP ecosystem. In this role, you will play a hands-on part in the development, customization, integration, and optimization of our NetSuite platform. You’ll partner closely with cross-functional teams across Finance, Operations, and Business Applications to create scalable and automated solutions that support our rapid growth.

Key Responsibilities

• Develop, test, and maintain custom scripts using SuiteScript 2.0 (and 1.0 where necessary) for automation, validation, and system extension.

• Build and optimize SuiteFlows, RESTlets, SuiteTalk APIs, and custom records to streamline operational and financial processes.

• Support configuration, customization, and administration of NetSuite modules, including ARM, SuiteBilling, Inventory, and Procurement.

• Create and maintain saved searches, dashboards, KPIs, and reports for business users and leadership visibility.

• Participate in integration efforts between NetSuite and third-party platforms such as Salesforce, Stripe, banks, and BI tools via middleware (e.g., Boomi, MuleSoft).

• Perform impact analysis and testing for system upgrades, new releases, and patch deployments.

• Collaborate with analysts, architects, and end users to gather requirements and translate them into scalable technical solutions.

• Write and maintain technical documentation, including design specs, test plans, and deployment runbooks.

• Apply best practices for development, testing, DevOps, and change management in NetSuite environments.

Qualifications

• 5+ years of NetSuite development experience with a strong technical foundation.

• Proven expertise in SuiteScript 2.0, SuiteFlow, SuiteTalk, saved searches, workflows, and RESTlets.

• Experience with NetSuite APIs (REST/SOAP) and middleware integration tools (Boomi, MuleSoft, Celigo, etc.).

• Deep understanding of key NetSuite processes such as Order-to-Cash, Procure-to-Pay, and Subscription Billing.

• Strong problem-solving skills and ability to independently drive complex technical projects.

• Excellent written and verbal communication skills; able to explain technical details to non-technical users.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent work experience.

Preferred Qualifications

• NetSuite Certifications: SuiteFoundation, SuiteCloud Developer, or Administrator.

• Experience with NetSuite ARM (Advanced Revenue Management) and SuiteBilling.

• Knowledge of NetSuite OneWorld (multi-entity, multi-currency, global tax setup).

• Exposure to Salesforce or other CRM integrations with NetSuite.

• Familiarity with SaaS models: usage-based billing, subscription management, and revenue recognition.

• Understanding of SOX compliance and controls in a public company.

• Experience working in Agile/Scrum environments and collaborating in cross-functional squads.

• Ability to mentor junior developers and contribute to code reviews and architecture discussions.

Tekion is pioneering the digital transformation of the automotive industry, a sector that has remained largely undisrupted for over five decades. Our flagship platform, the Automotive Retail Cloud™, is the first and fastest cloud-native solution of its kind, fundamentally re-engineering the end-to-end automotive retail experience. By leveraging vast datasets, sophisticated machine learning, and advanced AI, we are creating a seamlessly integrated ecosystem connecting OEMs, retailers, and consumers. We are a globally distributed team of technologists and innovators dedicated to solving complex, high Impact challenges.

The Position

Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
• Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
• Extensive experience implementing advanced neural network architectures.
• Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
• Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
• Proficiency with cloud computing platforms (GCP, Azure, AWS).
• Expertise in experimental design (A/B testing, causal inference).
• Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 11-14 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Perks and Benefits

• Competitive compensation
• Generous stock options
• Medical Insurance coverage
• Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies

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. Our Automotive Retail Cloud (ARC), Automotive Enterprise Cloud (AEC), and Automotive Partner Cloud (APC) connect OEMs, retailers, and consumers through one seamless platform. Utilizing cutting-edge technology, big data, machine learning, and AI, Tekion is transforming the automotive retail ecosystem. We're inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it with offices in North America, Asia, and Europe, Tekion employs around 3,000 people worldwide.

Tekion is pioneering the digital transformation of the automotive industry, a sector that has remained largely undisrupted for over five decades. Our flagship platform, the Automotive Retail Cloud™, is the first and fastest cloud-native solution of its kind, fundamentally re-engineering the end-to-end automotive retail experience. By leveraging vast datasets, sophisticated machine learning, and advanced AI, we are creating a seamlessly integrated ecosystem connecting OEMs, retailers, and consumers. We are a globally distributed team of technologists and innovators dedicated to solving complex, high Impact challenges.

The Position

Tekion seeks an exceptionally talented and seasoned Senior Staff Applied Scientist to architect the future of our AI-driven solutions. The incumbent will assume a pivotal role in our organization, providing the strategic and technical stewardship necessary to translate cutting-edge research into tangible business value. The ideal candidate is a first-principles thinker, adept at navigating ambiguity, and possesses the intellectual curiosity to formulate and solve complex, unstructured problems. This is a seminal opportunity to influence the trajectory of our AI strategy and deliver transformative solutions at an enterprise scale. 

Key Responsibilities

• Strategic Direction: Architect and execute the strategic vision for applied AI and Machine Learning within Tekion, ensuring rigorous alignment with overarching business objectives and industry challenges.
• Innovation & Research Leadership: Steer the R&D roadmap by identifying and capitalizing on emergent technological opportunities. Drive innovation through the ideation and implementation of novel, scientifically-grounded solutions.
• Stakeholder Alignment: Serve as the principal technical liaison between the R&D organization and executive stakeholders, ensuring technical strategies are congruent with business imperatives.
• Cross-Functional Execution: Lead collaborations with product, engineering, and business units to define, develop, and integrate sophisticated machine learning systems into core products and services.
• Scientific Contribution: Contribute to the broader scientific community through publications in premier academic conferences and journals, enhancing Tekion's position as a center of innovation.
• Mentorship & Talent Development: Mentor and cultivate a culture of scientific rigor and innovation among applied scientists, guiding project execution and fostering professional growth.
• Impact Quantification: Establish robust frameworks for model evaluation and performance measurement. Quantify and articulate the business impact of machine learning initiatives to executive leadership.
• Governance & Best Practices: Institute and govern best practices for the entire machine learning lifecycle, including model development, validation, deployment, and monitoring, while championing ethical and responsible AI

Core Competencies & Technical Expertise
The successful candidate will demonstrate mastery in the following areas:

• Foundational Expertise: Deep, theoretical and practical expertise in Machine Learning, Deep Learning, Causal Inference, and Explainable AI.
• Statistical Rigor: Advanced proficiency in applied probability and statistics to derive and validate insights from complex, high-dimensional data.
• Deep Learning:
  • Expert-level proficiency with frameworks such as TensorFlow, Keras, and PyTorch.
  • Extensive experience implementing advanced neural network architectures.
  • Practical application of Computer Vision (e.g., OpenCV) and Natural Language Processing (e.g., spaCy) methodologies.
• Large Language Models (LLMs): Demonstrated experience with Large Language Models, including advanced prompt engineering, fine-tuning, and deployment for specific business applications.
• Technical Proficiencies:
  • Advanced programming skills in Python and mastery of SQL. Familiarity with distributed computing frameworks (e.g., Spark) is advantageous.
  • Proficiency with cloud computing platforms (GCP, Azure, AWS).
  • Expertise in experimental design (A/B testing, causal inference).
  • Proficient in version control systems (Git).

Required Qualifications

• An advanced degree (Ph.D. or M.S. preferred) in a quantitative discipline such as Computer Science, Statistics, Operations Research, Physics, or a related field.
• A minimum of 11-14 years of post-academic experience in applied science or quantitative research roles, with a demonstrable history of translating complex models into tangible business value.
• A distinguished track record of solving difficult, business-critical problems using a scientific, data-driven approach.
• Proven experience in programming, data manipulation, and building models in a business context.
• Sophisticated data visualization and presentation skills, with the ability to distill complex analytical results into clear, actionable insights for diverse audiences.

Ideal Candidate Profile

• A profound intellectual curiosity and a systematic, first-principles approach to problem-solving.
• Domain expertise in the automotive industry or related fields such as finance or enterprise SaaS is highly desirable.
• Experience in specialized areas such as Recommendation Engines or advanced NLP is preferred.
• Exceptional communication and presentation capabilities, with a proven ability to distill complex technical concepts for executive-level audiences.
• A demonstrated ability to work collaboratively and effectively lead initiatives across multi-disciplinary teams.
• A commitment to continuous personal and team development within a collaborative, high-performance culture.

Overview 

 Tekion is entering its next phase of growth and is looking for a People Program Manager to support day-to-day People Program operations and help scale the infrastructure that powers our employee experience in India. 

 This is an individual contributor role focused on strong execution, program ownership, and operational excellence. You will partner closely with People Operations, People Partners, Talent Acquisition, Legal/Privacy, and Systems teams to deliver consistent, compliant, and employee centric People programs. For globally owned People programs, this role will serve as the India execution lead, responsible for localizing requirements, coordinating stakeholders, and ensuring successful delivery and adoption in India. 

 What you’ll do 

• Own and execute People programs end-to-end including performance management cycles, engagement surveys, internal talent movement programs, People/HR system upgrades, and compliance related initiatives. 
• Manage project delivery by building and maintaining project plans, timelines, milestones, dependencies, and status updates; proactively identify risks and drive mitigation. 
• Operationalize programs by supporting governance, operating rhythms, documentation, and handoffs to ensure programs are sustainable beyond initial launch. 
• Drive standardization and continuous improvement by maintaining core program artifacts (project charter, RACI, project plan, comms plan, launch readiness checklist, building repeatable playbooks/SOPs, and running post-launch retros to capture learnings and improve future cycles. 
• Create clear, scalable resources such as process guides, FAQs, templates, and manager communications to enable self-service and consistent execution. 
• Partner with Legal/Privacy and India compliance experts to ensure programs align with local statutory, audit, and data privacy requirements. 
• Maintain and analyze People data, including reporting, data audits, and basic dashboards to track program health and identify improvement opportunities. 
• Support the People team’s operating cadence, including preparation for Monthly and Quarterly Business Reviews and readiness for peak People cycles. 

What success looks like in this role 

• Core People programs and cycles run smoothly, on time, and with minimal escalations. 
• Stakeholders have clear visibility into timelines, ownership, and expectations for People & Cross-functional programs. 
• Processes and documentation are clear enough to enable consistent execution and increased self-service 
• The People team can rely on this role for strong operational follow-through and program readiness. 

 About you 

• A strong executor who brings structure to ambiguity and reliably follows through on commitments. 
• A process-oriented thinker who looks for practical improvements on that scale. 
• A collaborative partner who communicates clearly with cross functional stakeholders and balances people's needs with business priorities. 
• Detail oriented and organized with the confidence to raise risks and push back when needed. 

 Qualifications 

• 4–6 years of experience in HR/People Programs, HR/People Operations, HR/People Project Management, or related roles, ideally in a fast growing or mid to large organization. 
• Hands-on experience delivering cross-functional projects or recurring cycles (e.g., performance reviews, engagement surveys, system rollouts). 
• Working knowledge of project management tools (e.g., Jira, Microsoft Planner, Asana) and strong documentation practices. 
• Solid Excel or Google Sheets skills for reporting, tracking, and basic analysis of HR data. 
• Experience working with vendors or internal service providers to track deliverables and timelines. 
• Comfort collaborating with global stakeholders across time zones, including India–US teams. 

Preferred Qualifications:

• Exposure to India compliance topics (e.g., statutory processes, audits) through partnership with subject matter experts 
• Experience with People systems such as Workday (or equivalent HRIS), Greenhouse or Ashby (ATS), or similar tools. 
• Formal project management training or certification (PMP, Prince2, or equivalent). 

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact. 

Why this Role Matters 

• Accelerate the rollout of LLM-powered and agent-driven features across Tekion products. 

• Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders. 

• Operationalize secure, compliant, and explainable LLM and agentic services at scale. 

• Convert Applied Sciences models into scalable, compliant, cost‑efficient production services. 

• Standardize how models are trained, validated, deployed, and monitored across Tekion products. 

• Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference. 

What You’ll Do 

• Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts. 

• Integrate with the LLM Gateway/MCP, prompt/config versioning. 

• Build and orchestrate CI/CD pipelines. 

• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality. 

• Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems. 

• Monitor, detect, and mitigate risks unique to LLMs and agentic systems. 

• Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics. 

• Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph. 

• Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets. 

• Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage. 

• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking. 

• Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation. 

• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path. 

Desired Skills and Experience 

• 8 - 10 years in ML engineering/MLOps or backend/platform engineering with production ML. 

• Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores. 

• Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing. 

• Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.). 

• Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns. 

• Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices. 

• Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering. 

• Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection. 

• Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots. 

• Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience. 

• Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability. 

Preferred Mindset 

• Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics. 

• Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs. 

• Systems thinker: You design for multi-tenant scale, portability, and cost efficiency. 

• Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach. 

• Pragmatic: You automate the 80% and leave room for rapid experimentation.