Senior Director of Software Engineering - Java, AWS, RESTful, Containers

JPMorgan Chase & Co.; Hyderabad; On-site; INR 30,000,000 - 45,000,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Senior Director of Software Engineering in Hyderabad. You will lead cross-functional teams to drive large-scale engineering programmes, focusing on AI/ML and Data Governance.

Your role includes defining strategy, mentoring technical managers, and enhancing engineering practices across multiple teams. The ideal candidate has strong technical expertise and extensive experience in project delivery.

Qualifications

• 15+ years of experience in technical project delivery with 5+ years at Director level.
• Ability to navigate full stack conversations and assess architecture diagrams.
• Exceptional communication skills for non-technical stakeholders.

Responsibilities

• Define and own the delivery strategy and roadmap for large-scale engineering programmes.
• Accountable for quality and production stability, including test automation.
• Mentor and develop technical managers, establishing a leadership pipeline.

Skills

End-to-end technical project/programme delivery

API design (REST, gRPC, GraphQL)

AWS cloud infrastructure (EKS, networking)

CI/CD pipelines

Container orchestration (Kubernetes, Docker)

Agile methodologies

Tools

CI/CD tools

Observability tooling (Datadog, CloudWatch)

Databases (PostgreSQL, Neo4j)

Job description

Senior Director of Software Engineering - Java, AWS, RESTful, Containers

Job Information

• Job Identification 210741851
• Job Category Software Engineering
• Business Unit Corporate Sector
• Posting Date 06/12/2026, 05:58 AM
• Locations MAGMA,UNIT-1,PHASE-IV,SY NO.83/1,PLOT NO 2, GR Floor TO 2 Floor and 5 Floor TO 16 Floor,Basement 1,2, Hyderabad, IN-TG, 500081, IN
• Apply Before 06/14/2026, 06:30 PM
• Job Schedule Full time

Job Description

Your opportunity to make a real impact and shape the future of financial services is waiting for you. Lets push the boundaries of whats possible together.

As a Senior Director of Software Engineering at JPMorganChase within the Chief Data and Analytics Organization, you lead multiple technical areas, manage the activities of multiple teams, and collaborate across technical domains. Your expertise is applied cross-functionally to evolve firm wide Data Mesh, AI/ML and GenAI, and Data Governance platform. You will play a pivotal role in driving and delivering the strategic objectives, and will collaborate with many cross-functional teams to deliver scalable, high-performance, and user-centric platform. Your expertise will guide the development of key platform components and frameworks that align with the strategic goals of the organization.

Job responsibilities

• Define and own the delivery strategy and roadmap for large-scale, cross-team engineering programmes from planning and resourcing through risk management, dependency tracking, and stakeholder communication. Serve as the primary interface between Engineering, Product, and Executive leadership on programme status, trade-offs, and escalations.
• Partner with Principal Engineers and Architecture leads to translate technical vision into actionable delivery plans with clear milestones.
• Lead delivery through periods of organisational or technical change, including platform migrations, team restructures, and process transitions, maintaining momentum and morale.
• Accountable for quality and production stability, encompassing test automation strategy, performance benchmarking, release readiness, incident management, and SLA adherence.
• Establish and refine delivery frameworks, governance models, and reporting cadences appropriate for the scale and complexity of each programme.
• Identify systemic delivery risks early, including technical debt, resource gaps, and cross-team dependencies, and drive resolution before they become blockers.

Drive continuous improvement in engineering delivery practices, including retrospectives, delivery metrics, cycle time analysis, and process optimisation.

• Mentor and develop technical managers and delivery leads, building a strong leadership pipeline within the engineering organisation.
• Set and scale multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorised tools within the work environment) to drive firm-wide objectives (speed, scalability, reliability, cost-to-serve), including portfolio-level standards for AI-orchestrated delivery workflows, release governance, automated test modernisation, resilience engineering, and incident response acceleration; establish guardrails for validation, security, resiliency, traceability, and reuse.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorised AI-assisted development and automation capabilities, to drive cross-domain reuse and measurable capacity unlock outcomes across departments.

Required qualifications, capabilities, and skills

• 15+ years of experience in end-to-end technical project/programme delivery, with 5+ years at Director level.
• Proven track record delivering complex, multi-team programmes on time and at scale.
• Comfortable navigating conversations across the full stack, including API design (REST, gRPC, GraphQL), AWS cloud infrastructure (EKS, networking, serverless, IAM), CI/CD pipelines, container orchestration (Kubernetes, Docker), event streaming (Kafka, Kinesis), CDN strategies, front-end ecosystem, observability tooling (Datadog, CloudWatch, SLOs/SLIs), databases at scale (PostgreSQL, Neo4j), security and compliance, and QA automation strategies.
• Able to read and critically assess architecture diagrams and documentation, both front-end and back-end, challenge assumptions, and ask incisive questions in design reviews with technical fluency to evaluate architectural trade-offs: consistency models, service boundaries, cost vs resilience, build vs buy, and hold engineering teams accountable for sound decisions without needing to dictate the solution.
• Fluent in modern delivery methodologies (Agile, Scrum, Kanban) with the pragmatism to adapt frameworks to context rather than enforce rigid process.
• Exceptional communication skills: able to distil engineering complexity into clear, concise narratives for non-technical stakeholders at all levels.
• Effective at building consensus and driving outcomes across organisations with competing priorities.
• Track record of building and developing high-performing delivery teams.
• Skilled at influencing without authority, earning trust from engineers, product owners, and executives alike.
• Experience leading multi-organisation adoption of agentic AI-enabled engineering operating models (using enterprise-authorised tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.
• Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.