About JazzX AI Builder Studio 

JazzX AI Builder Studio is an enterprise AGI builder platform designed to empower builders to rapidly build, validate, and deploy production-grade AGI solutions with confidence. 

Builder Studio provides a unified, modular environment where teams compose reusable components, leverage domain-aware reasoning, and apply rigorous evaluation and governance workflows. With built-in capabilities for evaluation, explainability, and domain intelligence, Builder Studio enables enterprises to scale AI adoption across complex, high-stakes domains with reduced risk and significantly higher productivity, with an AI-native approach for Builders optimizing for speed, accuracy, flexibility and reusability. 

Role Overview 

Builder Studio owns a large, high-impact execution surface within Builder Studio, partnering closely with the stakeholders to bring the overall product vision to life. 

This role focuses on how the platform works in practice for builders and solution teams - ensuring that reusable components, evaluation systems, and domain intelligence come together into coherent, scalable workflows. 

Rather than defining the entire platform narrative, this PM is responsible for turning strategy into durable systems that compound value across solutions, customers, and domains. 

What You’ll Own 

Platform Systems & Execution Ownership 

• Own one or more major platform capability areas (e.g. reuse & solutioning workflows, AI quality systems, domain intelligence enablement), with scope evolving over time. 

• Translate platform strategy into clear product requirements, milestones, and delivery plans. 

• Ensure platform primitives are composable, extensible, and production-ready. 

• Partner with engineering to manage tradeoffs around flexibility, correctness, and backward compatibility. 

Reuse, Leverage & Solutioning Workflows 

• Enable builders to assemble solutions using reusable components instead of starting from scratch. 

• Define workflows for packaging, discovering, adapting, and versioning of reusable assets. 

• Reduce friction in customizing templates for customer- and domain-specific needs. 

• Help turn repeated solution patterns into first-class platform capabilities. 

AI Quality, Evaluation & Debugging 

• Help productize AI evaluation as part of normal builder workflows. 

• Define quality signals, regression detection, and drift monitoring surfaces to builders. 

• Enable debugging workflows that rely on evaluation signals, comparisons, and diffs—not just logs. 

• Ensure quality systems support enterprise trust, auditability, and governance needs. 

Domain Intelligence Enablement 

• Support workflows for configuring and evolving domain logic, reasoning systems, and knowledge assets. 

• Ensure domain intelligence integrates cleanly with solutioning, evaluation, and deployment systems. 

• Help solution engineers and domain experts collaborate without excessive custom engineering. 

• Promote reuse of domain intelligence across workflows and customers. 

Builder Experience & Adoption 

• Advocate for builder productivity and clarity across platform workflows. 

• Ensure smooth progression from sandbox experimentation to production deployment. 

• Continuously identify and remove friction in day-to-day solution building. 

• Validate product decisions through close collaboration with forward deployment and solution teams. 

Cross-Functional Collaboration 

• Partner closely with the Platform Lead to align execution with the overall product strategy. 

• Work day-to-day with engineering, design, AI research, and forward deployment teams. 

• Bring structured thinking and clarity to complex, ambiguous problem spaces. 

• Help drive prioritization and sequencing across competing platform investments. 

What We’re Looking For 

• 8 to 10 years of product management experience, ideally on platforms, developer tooling, or enterprise systems. 

• Strong execution mindset with the ability to own complex systems end-to-end. 

• Comfort working with AI-powered systems (agents, workflows, evaluation, or reasoning), without requiring deep research specialization. 

• Ability to reason for tradeoffs between flexibility, reuse, quality, and governance. 

• Proven ability to partner with senior PMs and engineering leaders. 

• Clear communicator who can turn ambiguity into structured plans. 

Role Overview

The Senior Product Manager – Residential Mortgage is an individual contributor who is customer-facing and focused on supporting the successful market adoption of JazzX’s AI-powered Residential Mortgage application. This role works closely with Product leadership, Sales, and Marketing to help translate product capabilities into clear customer value and effective go-to-market execution.

The Senior Product Manager contributes to product launches, customer engagement, messaging refinement, and field enablement, while serving as a strong conduit for customer and market feedback back into the product organization. This role plays an important role in executing against the Go-To-Market strategy with rigor and clarity.

This position is well-suited for a product manager with solid residential mortgage domain experience who is ready to operate in complex enterprise environments.

Core Responsibilities

Product Go-To-Market Support

• Support product go-to-market execution for JazzX’s Residential Mortgage application in partnership with Product leadership, Sales, and Marketing.
• Assist with launches by helping prepare customer-facing materials, enablement assets, and internal readiness documentation.
• Help ensure new capabilities are introduced with clear use cases, value propositions, and adoption guidance.

Product Messaging & Enablement

• Contribute to the development and refinement of product messaging and positioning.
• Help translate mortgage workflows, compliance requirements, and AI-driven functionality into clear, accurate customer-facing narratives.
• Support creation and maintenance of sales enablement materials such as pitch decks, demo flows, FAQs, and product documentation.

Customer & Market Engagement

• Participate in customer meetings, demos, pilots, and feedback sessions as a product representative.
• Support customer discovery efforts to understand operational pain points, adoption challenges, and feature gaps.
• Capture and synthesize customer feedback to share with Product leadership, Sales, and Marketing.

Launch & Readiness Execution

• Assist in coordinating launch activities across product, engineering, marketing, and field teams.
• Help track launch readiness tasks and follow up on post-launch feedback and adoption signals.
• Support continuous improvement of messaging and enablement based on customer and field input.

Competitive & Market Awareness

• Maintain awareness of competitive mortgage technology solutions and industry trends.
• Help gather and organize competitive insights to support positioning and sales conversations.
• Escalate notable competitive patterns or risks to product leadership.

Qualifications

Experience

• 5–8+ years of experience in product management, product marketing, solutions consulting, or related roles.
• Residential mortgage experience is required, with familiarity across workflows such as origination, underwriting, processing, closing, and post-close.
• Experience working with enterprise customers or supporting complex B2B sales cycles is strongly preferred.

Domain & Technical Acumen

• Solid understanding of residential mortgage processes, terminology, and regulatory considerations.
• Familiarity with enterprise SaaS products and workflow-driven systems.
• Exposure to AI-enabled products is preferred, with the ability to explain capabilities clearly and responsibly.

Skills & Attributes

• Strong written and verbal communication skills.
• Comfortable engaging with customers and internal stakeholders in structured settings.
• Organized, detail-oriented, and able to manage multiple initiatives in parallel.
• Demonstrated ability to learn quickly and operate effectively in evolving environments.

Education

• Bachelor’s degree in Business, Engineering, Computer Science, or a related field required.
• Advanced degree (MBA or equivalent) is a plus.

Role Overview 

As a Part‑Time Residential Mortgage Loan Underwriter Consultant at JazzX AI, you will leverage your deep expertise in underwriting to build AI-technology to support mortgage underwriting activities. You will work closely with engineering, and product teams to convert real-world underwriting decisions into robust AI logic. 

Contract Duration: 6 months (potential to extend up to 12 months) 

Key Responsibilities:

• Underwriting & File Assessment
  • Underwrite a variety of residential mortgage loan files (purchase, rate‑term refinance, cash‑out refinance) per Fannie Mae DU and Freddie Mac LP guidelines.
  • Document underwriting rationale, risk profiles, and exception handling. 

• Process Mapping & Rule Development
  • Deconstruct end-to-end underwriting workflows—from borrower qualification and income/asset verification to AUS findings and final approval.
  • Identify critical decision points and edge cases crucial for AI modeling. 

• Model Validation & Feedback
  • Blind-test AI-generated underwriting recommendations against manual assessments.
  • Provide granular feedback to engineering teams to fine-tune decision rules and confidence thresholds. 

• Knowledge Transfer & Training
  • Create clear, actionable guides on complex topics (e.g., compensating factors, manual AUS overrides, GSE compliance).
  • Host virtual workshops or Q&A sessions to transfer domain knowledge to cross-functional teams. 

Required Qualifications 

• Experience: 4–10 years in residential mortgage underwriting at a senior or specialist level.
• GSE Mastery: Deep, hands-on knowledge of Fannie Mae DU and/or Freddie Mac LP guidelines.
• Analytical Acumen: Proven ability to assess borrower credit, income, assets, and collateral with accuracy and consistency.
• Communication: Exceptional verbal and written skills to articulate underwriting logic and decision processes.
• Consulting Approach: Comfortable in an iterative environment, providing structured feedback to product and engineering teams. 

Preferred Qualifications 

• Experience at large retail or independent mortgage lenders (e.g., Wells Fargo, Rocket Mortgage, Chase).
• Background in manual underwriting, AUS overrides, or secondary market delivery.
• Familiarity with post-closing QC, servicing reviews, and secondary market delivery processes.
• Prior involvement in technology or automation initiatives within mortgage operations. 

Role Overview

This role leads the productization of the Reasoning Platform driving definition and delivery of the core reasoning capabilities underpinning the JazzX AGI system. This covers a wide spectrum of reasoning approaches from neuro-symbolic, probabilistic, cognitive, reinforcement-learning (RL)-based reasoning systems, as well as the infrastructure, tooling, and evaluation frameworks required to build, train, validate, and continuously improve AGI reasoners. The role owns strategy across data curation, benchmarking, feature alignment with customer use cases, RL gym environments, safety constraints, and tools enabling forward deployment teams to design, evaluate, and refine reasoning behaviors at scale.

The position works closely with research, engineering, safety, design, forward-deployment teams, and enterprise domain experts to ensure reasoning is predictable, verifiable, explainable, and aligned with real-world needs.

Core Responsibilities

Product Strategy

• Define the roadmap for the Reasoner Platform spanning the full spectrum of reasoning systems.
• Set product direction for prioritized feature development aligned with customer use cases and value drivers.
• Drive strategy for evaluation, safety constraints, reward models, and benchmarking systems improving reasoning accuracy, stability and reliability.

Reasoner Platform Productization

• Define requirements for configurable RL gym environments used to train, test, and validate agentic behaviors.
• Convert advanced reasoning research into productized capabilities, APIs, and developer tools for forward deployment teams to build customer solutions.
• Partner with research and engineering to deliver scalable training and inference infrastructure for reasoning-centric workloads.

Data Curation & Benchmarking

• Lead strategy for datasets, scenarios, and evaluation frameworks that measure reasoning accuracy, robustness, alignment, and generalization.
• Define requirements for synthetic data generation, curated reasoning traces, and adversarial testing.
• Own the roadmap for benchmarking tools, dashboards, leaderboards, and automated evaluation pipelines.

Reasoner Builder & Developer Experience

• Deliver tools that enable teams to design, test, refine, and deploy custom reasoning patterns.
• Define interfaces for rule editing, prompt program construction, policy tuning, and RL reward configuration.
• Ensure builder workflows support rapid iteration, safe experimentation, and interpretable outputs.

Integration with AGI Capabilities

• Align reasoning capabilities with memory, grounding, planning, and the broader Knowledge Platform.
• Define safe mechanisms for reasoners to inspect state, update plans, call tools, interact with environments, and refine policies.
• Integrate provenance, safety checks, transparency, and control mechanisms across all reasoning operations.

Customer & Domain Alignment

• Partner with enterprise domain specialists to understand complex decision workflows and map them to reasoning primitives.
• Identify common reasoning patterns across industries and convert them into reusable platform components.
• Ensure the platform supports both autonomous agents and human-in-the-loop decision processes.

Metrics & Impact

• Define and track core reasoning KPIs such as correctness, robustness, consistency, sample efficiency, safety adherence, and generalization.
• Measure performance across synthetic, human-generated, and real-world tasks.
• Use evaluation insights to refine roadmap priorities and ensure platform impact translates to real-world performance.

Qualifications

Experience

• 10+ years in technical product management; 5+ years in AI/ML, agent systems, RL, or reasoning technologies.
• Experience building large-scale AI platforms, RL training systems, evaluation frameworks, or advanced decision-support tools.
• Demonstrated success in productizing research-heavy technologies.

Technical Depth

• Strong understanding of RL, policy optimization, reward modeling, agentic planning, and model fine tuning approaches.
• Knowledge of evaluation methods, benchmarking design, dataset development, and safety frameworks.

Leadership

• Ability to lead multi-year product strategy across research and engineering.
• Skilled at turning emerging reasoning research into stable, scalable platform features.
• Ability to mentor senior PMs across data curation, model-based reasoning, and builder experiences.

Education

• Bachelor’s degree in Computer Science, Engineering, or a related technical field required. Advanced degrees (MS, PhD) in relevant areas preferred but not required.

Technical Product Manager, Innovation: Role Overview

Role Summary

JazzX is building AI-native digital workers that operate with institutional intelligence—governed, explainable, and continuously improving in real production environments. As JazzX expands beyond residential mortgage into new high-stakes domains (e.g., commercial lending, insurance, and adjacent verticals), the ability to rapidly stand up domain-specific solutions is a critical growth lever.

The Technical Product Manager, Innovation is a foundational product role responsible for accelerating JazzX’s reach into new verticals. This TPM will create reusable solutions as well as solution accelerators (e.g. workflow templates, policy and controls packs, ontologies, integration patterns, agent configurations, evaluation harnesses, etc.), and demo-ready reference implementations—that compress time-to-value across commercial lending, insurance, and future domains.

This is a hybrid builder-deployer role. You will combine deep product thinking with hands-on customer engagement—at times, working directly within customer organizations to implement JazzX solutions in production. Every deployment strengthens the accelerator library and platform, so the next one is faster, cheaper, and better. Think part technical product manager and part solutions architect—with the strategic judgment to shape what JazzX builds next based on what you learn in the field.

This is a 0 → 1 → scale role: hands-on execution early, then systematizing what works into playbooks, templates, and reusable platform capabilities.

Core Profile: What We Need

0 → 1 Builder With Systems Thinking (Startup DNA, High Ownership)

Thrives in ambiguity and can go from blank page to shipped solution fast—then turn one-off success into a repeatable template that scales across customers and verticals. You build the “factory,” not just the first widget. Balances speed with enterprise-grade quality in high-stakes environments.

Technical Product Leader (Strong Engineering Surface Area)

Comfortable going deep on APIs, AI & data models, integrations, permissions, system boundaries, and deployment constraints. Able to partner as a technical peer to Engineering: clarify tradeoffs, shape architecture decisions, and keep execution unblocked. Writes crisp technical specs, defines interfaces, validates edge cases, and understands what it takes to ship production-grade software. Strong instincts around instrumentation, telemetry, reliability, and operational workflows.

Solution Accelerator & Template Architect (Reuse as a First-Class Goal)

Thinks in modular building blocks: repeatable workflow patterns, configurable policies, reusable connectors, reference ontologies, evaluation harnesses, and deployable blueprints. Can distinguish what should be productized in the core platform vs. what should live as a domain package or configuration layer. Obsessed with repeatability and scale—every implementation should make the next one faster.

AI-Native Product Thinking

Experience building AI-powered workflows where systems complete consequential work and humans supervise outcomes. Comfortable with concepts like:

• Human-in-the-loop controls and escalation
• Explainability, confidence signaling, and audit trails
• Exception handling, recoverability, and safe automation
• Task orchestration, tool/function calling, guardrails, and continuous improvement loops

Domain Agility Across Regulated Enterprises

Prior experience in one or more regulated verticals such as Lending and/or Insurance is strongly preferred—but rapid learning and structured problem-solving are the true requirements.

Customer-Embedded Deployment Mindset (Production-Oriented Delivery)

Comfortable working directly with customer stakeholders (business and technical) to translate needs into shipped, measurable outcomes. Can operate effectively inside customer constraints: legacy systems, security reviews, data quality issues, governance, and change management. Treats adoption and measurable ROI as the job, not a downstream concern.

Clear Communicator & Cross-Functional Driver

Able to produce crisp product specs, workflow diagrams, decision logs, and rollout plans. Can lead alignment across Product, Engineering, UX, Solutions/Delivery, and GTM. Synthesizes field observations into clear, actionable product insights—serving as the critical bridge between customer reality and JazzX’s product roadmap.

Role Scope: What This Leader Will Drive

1. Identify and Prioritize New-Domain Solution Requirements

• Conduct deep domain immersion for each new vertical: understand the regulatory landscape, key personas, decision workflows, data requirements, and competitive dynamics
• Map the highest-leverage workflows and “thin slices” that prove value quickly in each segment
• Define segment-specific solution roadmaps (e.g., commercial lending sub-products; insurance lines/workflows) with clear value theses and measurable outcomes
• Conduct competitive analysis to understand how incumbents serve each segment and identify JazzX’s differentiated entry points

1. Build a Library of Templates & Solution Accelerators

Create reusable assets that materially shorten time-to-value, including:

• Workflow blueprints and reference architectures
• Configuration templates (policies, routing, exception paths, controls)
• Canonical data models and mapping guides
• Agent behavior configurations, prompt templates, and orchestration patterns
• Integration patterns/connectors and deployment checklists
• Evaluation and QA harnesses (golden datasets, regression tests, human review loops)
• Demo-ready “starter kits” that are real enough to become production

Package accelerators so they can be deployed repeatedly with predictable effort. Define what “good” looks like: measurable success criteria, instrumentation requirements, operational KPIs, and audit readiness.

1. Own End-to-End Customer Delivery for Selected Deployments

• Serve as JazzX’s forward-deployed technical partner within customer environments during initial solution rollouts
• Lead discovery, scoping, and solution design; map customer-specific workflows, data flows, and operational nuances; configure and adapt JazzX solutions accordingly
• Work alongside customer operations, IT, security, compliance, and business stakeholders to validate solution performance and drive adoption
• Ensure solutions move beyond pilots into production with reliability, governance, and measurable ROI built in
• Capture and productize learnings into the accelerator library—so every deployment makes the next one faster

1. Convert Workflow Reality Into Shippable Product Requirements

• Write detailed PRDs/specs that are precise on: user journeys, data/permission needs, integration contracts, edge cases, failure modes, and audit requirements
• Identify platform gaps exposed by new domain requirements and advocate for platform investments that increase cross-domain leverage
• Partner tightly with Engineering and UX to ship with high quality (including QA, release readiness, and instrumentation)
• Maintain a pragmatic backlog balancing domain accelerators, platform improvements, and customer-critical delivery needs

1. Ensure Trust, Governance, and Enterprise-Grade Controls

• Build patterns for explainability, auditability, supervision, and recoverability across all deployed solutions
• Define the human-in-the-loop controls: review, approve, intervene, escalate, and learn from expert judgment
• Partner with Security/Compliance stakeholders to meet customer requirements (roles/permissions, logs, data handling, policy enforcement)
• Design for enterprise reality: approvals, audit trails, governance, and integration into existing tools and operating rhythms

1. Establish Outcome Metrics and Continuous Improvement Loops

• Define success metrics per accelerator (time saved, throughput, error reduction, SLA adherence, audit readiness, user adoption)
• Ensure solutions are instrumented so JazzX can observe performance and iterate quickly
• Drive post-deployment iteration cycles that improve both the customer solution and the reusable template
• Maintain a domain knowledge base that enables future team members and customer success teams to deploy solutions independently

1. Enable Internal Teams & Support Go-to-Market

• Create internal documentation, demo flows, and enablement materials for Solutions, Sales, and Customer Success
• Partner with Marketing to develop domain-specific demos, proof-of-value frameworks, and customer-facing materials
• Contribute domain expertise to RFP responses, prospect conversations, and strategic partnership discussions
• Help build referenceable customer success stories with quantified outcomes from deployed solutions
• Represent JazzX’s domain expertise at industry events, conferences, and customer forums

Success Outcomes (First 12–18 Months)

Foundation & First Accelerators (0–6 Months)

• Deep domain immersion completed for at least two new verticals (e.g., commercial lending and insurance) with documented workflow maps, persona profiles, and opportunity assessments
• First set of new-domain use cases prioritized with clear ROI hypotheses and measurable success metrics
• 1–2 production-grade accelerators shipped (or in late-stage pilot) with documented templates, configuration patterns, and deployment checklists
• At least one customer-embedded deployment initiated with active workflow mapping and solution configuration underway
• Repeatable discovery-to-implementation workflow established (intake → spec → build → deploy → measure → templatize)

Expansion & Repeatability (6–12 Months)

• A growing library of accelerators spanning multiple segments within at least one new domain (e.g., multiple commercial lending sub-products or multiple insurance workflows)
• Time-to-value meaningfully reduced for subsequent deployments because templates, integration patterns, and evaluation harnesses are reusable
• At least two customer-embedded deployments delivering production value with quantified ROI outcomes
• Clear feedback loop from customer deployments into platform roadmap (what must be standardized vs. configured vs. left as customer-specific)

Scale & Platform Leverage (12–18 Months)

• A durable “solution factory” motion: new accelerators can be created and deployed predictably, without reinventing core patterns each time
• Deployment playbooks and domain knowledge base mature enough to enable other team members to execute deployments with decreasing direct involvement
• Multiple customer deployments leveraging the accelerator library with strong adoption and measurable outcomes
• Referenceable customer success stories across multiple domains with quantified business impact
• JazzX recognized by customers as enterprise-ready in new domains—due to governed operation, explainability, and real workflow embedding—not just a horizontal AI tool, but a solution that understands the business

Staff AI Product Manager – Core AGI Platform Services 

Location:  Bangalore, India (with availability to work across multiple time zones) 

Department: Product Management (Technical) 

Role Overview 

As a Staff AI Product Manager (Technical) for Core AGI Platform Services, you will own the foundational services that power reasoning, orchestration, memory, safety, and scalability across all AGI-enabled products. This role is responsible for defining and evolving platform-level capabilities ensuring research breakthroughs translate into reliable, reusable, enterprise-grade services. The position requires deep technical judgment, system-level thinking, and the ability to productize AGI capabilities under real-world constraints. 

Responsibilities 

Product Strategy & AGI Roadmap 

• Define and maintain the roadmap for Core AGI Platform Services, including reasoning, agent orchestration, memory, and model interaction layers. 

• Align platform priorities with the long-term AGI vision, focusing on extensibility, composability, and reuse across products. 

• Anticipate platform needs for emerging AGI capabilities such as long-horizon reasoning, autonomous agents, continual learning, and alignment controls. 

• Establish clear interfaces and ownership boundaries between core services and downstream solution teams. 

Cross-Functional Leadership 

• Partner closely with AGI research teams to transition experimental capabilities into production-grade platform services. 

• Collaborate with platform and infrastructure engineering to ensure services are scalable, reliable, and operable across cloud, hybrid, and enterprise environments. 

• Work with security, safety, and ethics stakeholders to embed governance, policy enforcement, and auditability directly into platform services. 

• Provide technical product leadership across time zones, driving alignment without relying on hierarchical authority. 

Customer-Centric Innovation 

• Treat internal product and solution teams as primary customers of the platform. 

• Identify recurring infrastructure and capability gaps that slow AGI product development and consolidate them into shared services. 

• Incorporate feedback from enterprise deployments to harden platform primitives against real-world operational constraints. 

• Balance capability velocity with reliability, safety, and long-term maintainability. 

Metrics & Scalability 

• Define KPIs for platform health, including adoption, reliability, performance, cost efficiency, and reasoning quality. 

• Establish evaluation and observability mechanisms for AGI behaviors at the platform level. 

• Enable continuous experimentation while maintaining strict standards for production readiness and rollback. 

Go-to-Market Execution 

• Support internal and external enablement by providing clear platform contracts, documentation, and integration patterns. 

• Partner with customer-facing teams to ensure Core AGI Platform Services integrate cleanly into enterprise workflows. 

• Help articulate platform capabilities and constraints to technical and executive stakeholders without overpromising outcomes. 

Qualifications 

Experience 

• 8–12 years of technical product management experience, withdemonstratedownership of platform or infrastructure products. 
  • 3+ years delivering AI/ML or LLM-based systems used in production at scale. 
  • Experience operating in research-adjacent environments where ambiguity and rapid iteration are the norm. 

Technical Acumen 

• Strong understanding of foundation models, LLMs, agentic frameworks, RAG, and memory architectures.
  • Familiarity with large-scale model serving, distributed inference, and platform reliability concerns.
  • Ability to reason about system-level tradeoffs involving latency, cost, capability, and safety. 

Leadership & Strategy 

• Proven ability to translate research outputs into durable platform capabilities.
  • Comfortable making high-impact platform decisions with incomplete information.
  • Able to influence senior engineers, researchers, and executives through technical clarity and structured thinking. 

Soft Skills 

• Clear, precise communicator with the ability to explain complex platform concepts succinctly.
  • Strong analytical problem-solving skills with a bias toward decisive execution.
  • Operates effectively across global, cross-functional teams without dependency on formal authority. 

Education 

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; advanced degree preferred but not required.