7 Explainability Jobs

You will define AI/ML architectures, lead marquee customer engagements, and evangelize cutting-edge solutions in Generative AI (GenAI), Large Language Models (LLMs), AI Agents, and Responsible AI frameworks. The role demands a unique balance of strategic vision, hands-on technical delivery, and market-facing thought leadership. Job Title: Principal AI Architect - Consulting Technical Manager Location: India (Global role with cross-regional collaboration requires flexible time-zone support) Experience: 15-20 years total, with at least 8+ years in AI/ML solutioning and enterprise architecture Job Type: Full-time, Individual Contributor (Enterprise Architect calibre) Core Competencies Enterprise Architecture - Defining AI-enabled enterprise architectures that scale across industries. Generative AI & Agents - Proven expertise in LLMs, multi-modal AI, AI agent orchestration, and prompt/flow engineering. Cloud & Multi-cloud Strategy - Expert in Oracle Cloud Infrastructure (OCI) experience with AWS, Azure, GCP highly valued. AI/ML Engineering & MLOps - Strong grounding in ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow), CI/CD, observability, and governance. AI Security & Responsible AI - Knowledge of data privacy, fairness, explainability, model risk & compliance frameworks. Executive Engagement - Ability to communicate AI vision and ROI at board/executive level, while guiding technical teams on design/delivery. Innovation & GTM - Strong orientation towards IP reuse, accelerators, and GTM initiatives (proposals, bid defense, executive workshops). Qualifications & Experience 16-20 years in technology, with 8+ years in AI/ML, Data Science, or Advanced Analytics. Demonstrated track record in enterprise-scale AI/ML adoption-from discovery to production rollout. Proven hands-on expertise in GenAI, LLM fine-tuning, multi-modal AI, and intelligent agents. Deep experience with cloud-native deployments, vector databases, RAG architectures, and hybrid data pipelines. Strong expertise in MLOps, governance, and lifecycle management of AI models. Experience in executive-facing roles (CxO briefings, board-level AI strategy sessions). Bachelor's/Master's in Computer Science, Data Science, AI, or equivalent. PhD preferred but not mandatory. Contributions to AI thought leadership: patents, whitepapers, conference talks, or AI community initiatives. Key Responsibilities Enterprise AI Leadership Drive enterprise-wide AI/ML architecture strategy, ensuring alignment with business outcomes, data strategy, security, and compliance. Solution Design & Delivery Architect, prototype, and deliver production-grade AI systems across GenAI, LLMs, multi-modal AI, RAG pipelines, and intelligent agents. CxO Engagement Act as a trusted advisor to CIOs/CTOs/CDOs on AI adoption strategy, cloud-native transformation, and scaling AI beyond PoCs into production. Hands-on Technical Authority Remain deeply hands-on in architecting and integrating AI into enterprise landscapes (Fusion, EBS, custom apps, cloud-native stacks). Governance & Standards Establish AI architecture blueprints, reusable patterns, and governance frameworks (LLMOps, model risk management, AI security, EU AI Act compliance). Thought Leadership Represent the practice in customer-facing demos, conferences, and whitepapers influence Oracle's AI GTM and innovation roadmap. Cross-Studio Collaboration Partner with Cloud, Data & Analytics, and Security Studios to deliver end-to-end enterprise transformation solutions. Market & Innovation Focus Track global AI trends, vendor ecosystems (OpenAI, Cohere, Anthropic, HuggingFace), and continuously infuse market-leading innovation into delivery. Career Level - IC4

Job Description Be the accountable leader for AI and data governance in LRCO operationalizing Responsible AI, risk, and data management controls while partnering with Data Owners to shape and execute the LRCO data strategy. You are passionate about turning governance into an accelerator not a blocker. Youll lead the frameworks, processes, and data foundations that let teams ship compliant, explainable AI and analytics at scale. Join us to set the standard for safe innovation in Legal & Regulatory Control Operations, from intake to production, across ML, NLP, retrieval, GenAI and automation. Job Summary As the AI & Data Governance Lead for Legal & Regulatory Control Operations (LRCO) , you will own the operating model that keeps our AI/ML and data-driven capabilities compliant, measurable, and scalable. Youll run end?to?end governance (intake, risk assessment, approvals, monitoring, audit readiness) and co?own the LRCO data strategy with our Data Owners and partners covering data architecture, lineage, taxonomy, quality, and consumption patterns. Youll partner across Product, Engineering/ML, Legal, DUC, MRGR, and Data Owners to embed controls (privacy, explainability, fairness, security, HITL) and to align with firmwide standards so we can deliver measurable customer value without compromising safety or compliance. Job Responsibilities Leverage strong communication skills to lead project teams through challenges and work with key stakeholders (higher, peer, lower in the organizational structure) via influencing and negotiating. Own the AI governance strategy for LRCO and embed it into the product roadmap aligning to firmwide and CCB procedures (registration, approvals, monitoring, documentation). Run the AI/ML governance tollgates (registration, governance forums, etc.) and ensure change?management reviews where applicable. Present on model risk governance: For determination of Model vs Analytical Tool designation, track submissions/waivers, secure approvals, and set ongoing monitoring and documentation standards. Operationalize Responsible AI controls with Legal/CCOR (HITL, fairness/bias, explainability, privacy, security) and maintain compliance with prohibited AI checks and EU AI Act classifications. Co?own LRCOs data strategy with Data Owners covering architecture, taxonomies, metadata/lineage, store registration, gold source consumption and retention, and quality SLAs. Establish robust evaluation & monitoring: offline/online testing, quality metrics (precision/recall), bias/fairness reviews, red?teaming, security testing, drift/latency monitoring, and incident playbooks. Define standards for GenAI platform usage: prompt and knowledge base governance, vector store and content filter policies, audit logging, and HITL acceptance criteria. Reporting & transparency: publish governance dashboards (use?case pipeline, model inventory, risk posture, benefits realization) and brief leadership and auditors. Coach and enablement: deliver training and playbooks to uplift LRCO teams on governance, privacy, data quality, and evaluation practices. Required Qualifications, Capabilities, And Skills Minimum 8 years in data governance, risk, compliance, or product; 3+ years leading AI/ML or GenAI governance in regulated environments. Bachelors degree required; advanced degree in data/AI, risk, or related field. Deep knowledge of AI/ML governance and model risk processes (model vs. analytical tool designation, submissions, controls, monitoring). Proficient knowledge of the product development life cycle, Experience in product life cycle activities, including discovery and requirements definition. In-depth knowledge of Agile process and principles, including use of Agile project management tools (i.e., Confluence, JIRA, Git, etc.) Strong grasp of Responsible AI practices (HITL, privacy, fairness, explainability) and awareness of EU AI Act categories and prohibited AI checks. Proven experience partnering with Legal and risk teams to translate policy into product and control requirements. Expertise in data management (lineage, metadata, taxonomy, store registration, data quality) and working with Data Owners. Fluency with data risk and privacy standards (data classification, retention, personal information policies). Strong stakeholder management across Product, Engineering/ML, CDAO, and business leaders; excellent written/spoken communication. Metrics?driven: defines KPIs (accuracy/precision/recall, time?to?resolution, cost?to?serve, reliability/latency) and builds telemetry for continuous improvement. ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the worlds most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants and employees religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. Were proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions all while ranking first in customer satisfaction. Show more Show less

Be the accountable leader for AI and data governance in LRCO operationalizing Responsible AI, risk, and data management controls while partnering with Data Owners to shape and execute the LRCO data strategy. You are passionate about turning governance into an accelerator not a blocker. You'll lead the frameworks, processes, and data foundations that let teams ship compliant, explainable AI and analytics at scale. Join us to set the standard for safe innovation in Legal & Regulatory Control Operations, from intake to production, across ML, NLP, retrieval, GenAI and automation. Job summary As the AI & Data Governance Lead for Legal & Regulatory Control Operations (LRCO) , you will own the operating model that keeps our AI/ML and data-driven capabilities compliant, measurable, and scalable. You'll run end?to?end governance (intake, risk assessment, approvals, monitoring, audit readiness) and co?own the LRCO data strategy with our Data Owners and partners covering data architecture, lineage, taxonomy, quality, and consumption patterns. You'll partner across Product, Engineering/ML, Legal, DUC, MRGR, and Data Owners to embed controls (privacy, explainability, fairness, security, HITL) and to align with firmwide standards so we can deliver measurable customer value without compromising safety or compliance. Job responsibilities Leverage strong communication skills to lead project teams through challenges and work with key stakeholders (higher, peer, lower in the organizational structure) via influencing and negotiating. Own the AI governance strategy for LRCO and embed it into the product roadmap aligning to firmwide and CCB procedures (registration, approvals, monitoring, documentation). Run the AI/ML governance tollgates (registration, governance forums, etc.) and ensure change?management reviews where applicable. Present on model risk governance: For determination of Model vs Analytical Tool designation, track submissions/waivers, secure approvals, and set ongoing monitoring and documentation standards. Operationalize Responsible AI controls with Legal/CCOR (HITL, fairness/bias, explainability, privacy, security) and maintain compliance with prohibited AI checks and EU AI Act classifications. Co?own LRCO's data strategy with Data Owners covering architecture, taxonomies, metadata/lineage, store registration, gold source consumption and retention, and quality SLAs. Establish robust evaluation & monitoring: offline/online testing, quality metrics (precision/recall), bias/fairness reviews, red?teaming, security testing, drift/latency monitoring, and incident playbooks. Define standards for GenAI platform usage: prompt and knowledge base governance, vector store and content filter policies, audit logging, and HITL acceptance criteria. Reporting & transparency: publish governance dashboards (use?case pipeline, model inventory, risk posture, benefits realization) and brief leadership and auditors. Coach and enablement: deliver training and playbooks to uplift LRCO teams on governance, privacy, data quality, and evaluation practices. Required qualifications, capabilities, and skills Minimum 8 years in data governance, risk, compliance, or product 3+ years leading AI/ML or GenAI governance in regulated environments. Bachelor's degree required advanced degree in data/AI, risk, or related field. Deep knowledge of AI/ML governance and model risk processes (model vs. analytical tool designation, submissions, controls, monitoring). Proficient knowledge of the product development life cycle, Experience in product life cycle activities, including discovery and requirements definition. In-depth knowledge of Agile process and principles, including use of Agile project management tools (i.e., Confluence, JIRA, Git, etc.) Strong grasp of Responsible AI practices (HITL, privacy, fairness, explainability) and awareness of EU AI Act categories and prohibited AI checks. Proven experience partnering with Legal and risk teams to translate policy into product and control requirements. Expertise in data management (lineage, metadata, taxonomy, store registration, data quality) and working with Data Owners. Fluency with data risk and privacy standards (data classification, retention, personal information policies). Strong stakeholder management across Product, Engineering/ML, CDAO, and business leaders excellent written/spoken communication. Metrics?driven: defines KPIs (accuracy/precision/recall, time?to?resolution, cost?to?serve, reliability/latency) and builds telemetry for continuous improvement.

You will define AI/ML architectures, lead marquee customer engagements, and evangelize cutting-edge solutions in Generative AI (GenAI), Large Language Models (LLMs), AI Agents, and Responsible AI frameworks. The role demands a unique balance of strategic vision, hands-on technical delivery, and market-facing thought leadership. Job Title: Principal AI Architect - Consulting Technical Manager Location: India (Global role with cross-regional collaboration requires flexible time-zone support) Experience: 15-20 years total, with at least 8+ years in AI/ML solutioning and enterprise architecture Job Type: Full-time, Individual Contributor (Enterprise Architect calibre) Core Competencies Enterprise Architecture - Defining AI-enabled enterprise architectures that scale across industries. Generative AI & Agents - Proven expertise in LLMs, multi-modal AI, AI agent orchestration, and prompt/flow engineering. Cloud & Multi-cloud Strategy - Expert in Oracle Cloud Infrastructure (OCI) experience with AWS, Azure, GCP highly valued. AI/ML Engineering & MLOps - Strong grounding in ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow), CI/CD, observability, and governance. AI Security & Responsible AI - Knowledge of data privacy, fairness, explainability, model risk & compliance frameworks. Executive Engagement - Ability to communicate AI vision and ROI at board/executive level, while guiding technical teams on design/delivery. Innovation & GTM - Strong orientation towards IP reuse, accelerators, and GTM initiatives (proposals, bid defense, executive workshops). Qualifications & Experience 16-20 years in technology, with 8+ years in AI/ML, Data Science, or Advanced Analytics. Demonstrated track record in enterprise-scale AI/ML adoption-from discovery to production rollout. Proven hands-on expertise in GenAI, LLM fine-tuning, multi-modal AI, and intelligent agents. Deep experience with cloud-native deployments, vector databases, RAG architectures, and hybrid data pipelines. Strong expertise in MLOps, governance, and lifecycle management of AI models. Experience in executive-facing roles (CxO briefings, board-level AI strategy sessions). Bachelor's/Master's in Computer Science, Data Science, AI, or equivalent. PhD preferred but not mandatory. Contributions to AI thought leadership: patents, whitepapers, conference talks, or AI community initiatives. Key Responsibilities Enterprise AI Leadership Drive enterprise-wide AI/ML architecture strategy, ensuring alignment with business outcomes, data strategy, security, and compliance. Solution Design & Delivery Architect, prototype, and deliver production-grade AI systems across GenAI, LLMs, multi-modal AI, RAG pipelines, and intelligent agents. CxO Engagement Act as a trusted advisor to CIOs/CTOs/CDOs on AI adoption strategy, cloud-native transformation, and scaling AI beyond PoCs into production. Hands-on Technical Authority Remain deeply hands-on in architecting and integrating AI into enterprise landscapes (Fusion, EBS, custom apps, cloud-native stacks). Governance & Standards Establish AI architecture blueprints, reusable patterns, and governance frameworks (LLMOps, model risk management, AI security, EU AI Act compliance). Thought Leadership Represent the practice in customer-facing demos, conferences, and whitepapers influence Oracle's AI GTM and innovation roadmap. Cross-Studio Collaboration Partner with Cloud, Data & Analytics, and Security Studios to deliver end-to-end enterprise transformation solutions. Market & Innovation Focus Track global AI trends, vendor ecosystems (OpenAI, Cohere, Anthropic, HuggingFace), and continuously infuse market-leading innovation into delivery. Career Level - IC4

As a Principal Research Scientist focusing on AI Alignment at Ola Krutrim in Bangalore, India, you will lead the efforts in Trust and Safety, Interpretability, and Red Teaming within the AI division. Your role will be crucial in ensuring that the AI systems developed are safe, ethical, interpretable, and reliable, with a significant impact on millions of lives. You will be at the forefront of cutting-edge AI research, guiding the implementation of technologies that adhere to the highest standards of safety and transparency. Your responsibilities will include providing strategic leadership for the AI Alignment division, overseeing teams dedicated to Trust and Safety, Interpretability, and Red Teaming. You will work closely with the Lead AI Trust and Safety Research Scientist and Lead AI Interpretability Research Scientist to align goals and methodologies. Developing comprehensive strategies for AI alignment, integrating advanced safety and interpretability techniques, and establishing best practices for red teaming exercises to identify vulnerabilities will be key aspects of your role. Moreover, you will collaborate with product and research teams to implement safety and interpretability aspects throughout the AI development lifecycle. Staying updated on AI ethics, safety, and interpretability research, representing the company in industry events, and managing resource allocation and strategic planning for the AI Alignment division are also part of your responsibilities. Mentoring and developing team members, fostering innovation, and communicating progress and recommendations to executive leadership will be essential in this role. To qualify for this position, you should hold a Ph.D. in Computer Science, Machine Learning, or a related field with a focus on AI safety, ethics, and interpretability. With at least 7 years of experience in AI research and development, including 3 years in a leadership role, you should have expertise in AI safety, interpretability, and red teaming methodologies. Strong knowledge of advanced techniques such as Reinforcement Learning, Proximal Policy Optimization, and attention-based methods, along with experience in overseeing red teaming exercises for AI systems, are required. Your visionary mindset, along with excellent communication skills, project management abilities, and a proven track record in AI safety, ethics, and interpretability research, will be instrumental in shaping the future of responsible AI development at Ola Krutrim. By leading cross-functional initiatives and fostering a culture of continuous learning and innovation, you will contribute to building public trust in AI technologies and positioning the company as a leader in ethical and responsible AI development.,

As a Product Manager - Enterprise AI, you will play a crucial role in leading the transformation by defining and delivering AI tools that enhance voice intelligence, agent copilots, decision support systems, and risk engines. Your focus will be on supercharging our teams and establishing a new benchmark in fintech productivity. Your responsibilities will include defining the product vision and roadmap for our internal GenAI suite, which comprises voice copilots, risk intelligence agents, ops automation tools, regulatory AI assistants, and more. You will lead cross-functional teams to develop AI-powered workflows that reduce turnaround time, increase productivity, and enhance accuracy. Additionally, you will be responsible for making build vs. buy decisions utilizing vendors like OpenAI, Whisper, AssemblyAI, LangChain, among others. In this role, you will work hands-on with various AI technologies such as LLMs, embeddings, RAG pipelines, vector databases, and prompt tuning. It will be essential to design with explainability, fallback logic, and hallucination control as defaults. Monitoring success metrics like adoption rates, efficiency gains, and time saved will be crucial, and you will iterate quickly based on feedback to drive continuous improvement. Ensuring full alignment with regulatory bodies and internal compliance when deploying GenAI systems in critical workflows will be a key aspect of your role. You will also be responsible for maintaining cybersecurity standards as an integral part of product development, ensuring that products are built with security in mind from the outset. To be successful in this role, you should have at least 4+ years of product management experience, with at least 1 year in GenAI/ML/NLP-focused roles. A background in fintech, particularly in lending, collections, KYC, or regulatory operations, will be advantageous. A strong understanding of GenAI architecture, technical education background (in CS, Engineering, Data Science, or Applied Math), and experience working with data scientists, backend engineers, and legal/compliance teams are essential. An analytical mindset, the ability to define product KPIs, track outcomes, and excellent communication and stakeholder management skills are also crucial for excelling in this role.,

The Data Science Lead position at our company is a key role that requires a skilled and innovative individual to join our dynamic team. We are looking for a Data Scientist with hands-on experience in Copilot Studio, M365, Power Platform, AI Foundry, and integration services. In this role, you will collaborate closely with cross-functional teams to design, build, and deploy intelligent solutions that drive business value and facilitate digital transformation. Key Responsibilities: - Develop and deploy AI models and automation solutions using Copilot Studio and AI Foundry. - Utilize M365 tools and services to integrate data-driven solutions within the organization's digital ecosystem. - Design and implement workflows and applications using the Power Platform (Power Apps, Power Automate, Power BI). - Establish, maintain, and optimize data pipelines and integration services to ensure seamless data flow across platforms. - Engage with stakeholders to comprehend business requirements and translate them into actionable data science projects. - Communicate complex analytical insights effectively to both technical and non-technical audiences. - Continuously explore and assess new tools and technologies to enhance existing processes and solutions. Required Skills and Qualifications: - 5-12 years of overall experience. - Demonstrated expertise in Copilot Studio, M365, Power Platform, and AI Foundry. - Strong understanding of data integration services and APIs. - Proficient in data modeling, data visualization, and statistical analysis. - Experience with cloud platforms like Azure or AWS is advantageous. - Exceptional problem-solving and critical-thinking abilities. - Effective communication and collaboration skills. - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. Preferred Skills: - Familiarity with additional AI and machine learning frameworks. - Knowledge of agile methodologies and collaborative tools. - Certifications in Power Platform, Azure AI, or M365 are a plus. If you are a proactive and results-driven individual with a passion for data science and a desire to contribute to cutting-edge projects, we encourage you to apply for this challenging and rewarding opportunity as a Data Science Lead with our team.,