Top Tech Jobs & Startup Jobs

Build and productionize AI/ML, Generative AI, and agentic solutions on Databricks. Develop feature, training, and serving pipelines; create RAG systems and reusable accelerators; optimize jobs and workflows; and support governed, scalable production deployments. Collaborate directly with data scientists, architects, client engineering teams, and stakeholders to gather requirements, troubleshoot issues, and deliver documentation and runbooks.

Build and maintain Python services, APIs, configuration workflows, and reporting outputs for a GCP-based data platform. Responsibilities include managing versioned Firestore data, syncing to BigQuery, generating Excel reports, deploying services with Cloud Run and Cloud Storage, provisioning infrastructure with Terraform, maintaining CI/CD pipelines, applying IAM best practices, testing, troubleshooting, and collaborating with data engineers and stakeholders.

Leads technical solutioning and delivery for data and AI engagements, including discovery, target-state architecture, proposals, proofs of concept, Databricks lakehouses, production generative AI systems, CI/CD, infrastructure as code, testing, observability, and cost optimization. Provides hands-on implementation, client enablement, executive presentations, mentoring, production handover, and development of reusable architectures and accelerators. The role may also help recruit and lead a small delivery team.

Build production agentic AI solutions and reusable frameworks on Azure AI Foundry. Responsibilities include multi-agent orchestration, RAG knowledge repositories, reusable tools, Dataverse and Power Platform integration, governance, human approvals, evaluation, observability, security, and infrastructure-as-code deployments. The role requires strong Python and C#/.NET engineering skills, production LLM application experience, Azure expertise, and collaboration with business, technical, and risk stakeholders.

Owns enterprise ServiceNow ITSM backlog intake, refinement, prioritization, and delivery planning. Translates demand into implementable stories, facilitates process improvements, defines velocity and quality metrics, orchestrates UAT, and reports engagement performance to client leadership. Partners with process owners, operational leads, and platform architects to improve ITSM processes and establish a trusted advisory relationship.

Coordinates project delivery and business operations for a technology consultancy. Responsibilities include maintaining project plans, schedules, RAID logs, status reports, resourcing, timesheets, budgets, change control, documentation, contracts, onboarding, invoicing, compliance records, and internal processes. The role also supports finance, travel, meetings, and workflow automation using Power Platform and AI tools.

Develop and configure ServiceNow solutions focused on IT Asset Management, Hardware Asset Management, CMDB, Product Model, and enterprise data quality. Responsibilities include server- and client-side scripting, workflows, integrations, AI capabilities, data transformation, reporting, testing, troubleshooting, documentation, and client training. The role requires collaboration with architects, AI specialists, consultants, and stakeholders in Agile delivery environments.

Owns ingestion, data modeling, reconciliation, validation, and lineage for a financial billing platform on GCP. Designs auditable, idempotent BigQuery pipelines; implements data quality controls, quarantine processes, effective-dated reference data, and accurate monetary handling. Develops tested Python and advanced SQL, collaborates with engineering and finance stakeholders, and mentors team members. Preferred experience includes invoicing, regulated or audited finance environments, and additional GCP services.

Owns ingestion, data modeling, reconciliation, and lineage for a financial billing platform on GCP. Designs auditable, idempotent BigQuery pipelines; implements data quality, validation, quarantine, and reconciliation controls; handles monetary values accurately; and develops tested Python and advanced SQL. Collaborates with engineering, analytics, and finance stakeholders while mentoring team members and improving data engineering standards.

Build and enhance AI copilots using Microsoft Copilot Studio, integrating enterprise data, Microsoft 365, Power Platform, Dynamics 365, APIs, and third-party systems. Create conversational experiences, prompts, automations, and custom connectors; test and optimize solutions; implement security and governance; and collaborate with stakeholders to move Copilot use cases from concept to production. The role is fully remote in the Philippines or India and follows UK business hours.