Top Tech Jobs & Startup Jobs

Administer and configure OpenText ALM Octane environments, workflows, releases, pipelines, integrations, and permissions. Develop REST API automations, support Jira synchronization, migrate legacy ALM data, create reports, troubleshoot platform issues, enforce governance, document procedures, train users, and coordinate upgrades and integrations across engineering, QA, DevOps, and project teams.

Leads and mentors Java developers while designing, developing, testing, deploying, and maintaining scalable enterprise applications. Translates business requirements into technical solutions, troubleshoots issues, collaborates with cross-functional teams, and promotes innovation. The role requires strong Java expertise, knowledge of Agile and Scrum methodologies, familiarity with microservices and cloud computing, and effective communication and leadership skills.

Leads development and delivery of projects using emerging technologies, including AI, blockchain, and IoT. Provides technical guidance and mentorship, evaluates technology solutions, collaborates with cross-functional teams, and aligns initiatives with organizational strategy. The role requires software development expertise, knowledge of architecture and design patterns, strong leadership, communication, and continuous learning.

Design and maintain conceptual, logical, and physical data models for enterprise applications and warehouses. Translate business requirements into scalable data structures, dimensional models, and data dictionaries. Perform data profiling, quality assessments, validation, and database optimization. Collaborate with architects, ETL developers, DBAs, analytics teams, and business stakeholders while supporting governance, lineage, migration, integration, and modernization initiatives.

Enable enterprise adoption of Microsoft Copilot tools across US and UK teams. Assess AI opportunities, prioritize use cases, deliver training, build reusable agents, skills and prompts, and establish governance, documentation, ownership and support models. Integrate solutions with Microsoft 365 and Power Platform while addressing responsible AI, data protection, licensing and UK/EU data residency. Track adoption and business outcomes, coach team members, and complete a structured handover with playbooks and recommendations.

Designs and governs enterprise AI, generative AI, and automation solutions using Microsoft AI Foundry, Copilot Studio, Lyzr, Azure OpenAI, and Power Platform. Leads AI agent and copilot development, establishes governance, security, compliance, and responsible AI frameworks, develops architecture standards and documentation, and provides technical leadership to development teams and stakeholders.

Lead the design, training, fine-tuning, deployment, and monitoring of generative AI, large language model, retrieval-augmented generation, and multimodal systems. Build scalable cloud-based MLOps pipelines, optimize inference, conduct model evaluation and bias assessments, and support responsible AI, security, compliance, and audit readiness. Collaborate with data scientists, platform engineers, and business stakeholders while mentoring junior engineers and translating enterprise use cases into secure operational AI solutions.

Develop and maintain Dataverse-based enterprise applications using Power Apps, Power Automate, and Copilot Studio. Build AI-powered agents, autonomous workflows, and integrations with Microsoft 365, Teams, Planner, SharePoint, Dynamics CRM, and enterprise systems. Design secure, scalable, governed Power Platform solutions, support deployments, and drive continuous improvement. The role also requires Azure integrations, CI/CD experience, Agile delivery, and strong problem-solving skills in banking or financial services environments.

Designs, builds, migrates, and operates AWS workloads and platform infrastructure. Responsibilities include cloud architecture, infrastructure as code, security, cost optimization, environment provisioning, lifecycle management, DevOps and CI/CD, container platforms, and AI foundation enablement. The role uses Terraform, CloudFormation, AWS CDK, Python, Docker, Kubernetes, and numerous AWS services while applying the AWS Well-Architected Framework.

Define target-state enterprise data architecture, reusable data-product and medallion patterns, domain ownership boundaries, and migration roadmaps for a complex financial-services environment. The role covers data mesh, lakehouse platforms, reference and master data, stored-procedure decomposition, governance, contracts, lineage, risk assessment, and architecture documentation using TOGAF and ArchiMate or C4 models.