Valtech

Technical Project Manager

• Manage the customer service desk (Jira) for all incoming client tickets
• Triage and prioritize tickets, distinguishing operational tasks from development work
• Assign development tickets to the correct delivery team per client and follow up to resolution
• Resolve operational requests directly, including password resets, access provisioning, firewall rule changes, and WAF configuration
• Respond to client questions and keep tickets moving against agreed response times
• Monitor uptime across client websites and APIs (Pingdom) and manage alert routing (Opsgenie)
• Act as first responder for incidents, coordinating investigation and escalation for P1 events
• Coordinate with GSC India for 24x7 L1 support, briefing the nearshore team and handling escalations
• Perform biweekly system patching for client servers hosted on virtualised infrastructure
• Coordinate maintenance windows with clients and verify service health after changes
• Document maintenance activity through change tickets
• Run monthly software lifecycle and end-of-life reviews across client technology stacks
• Review newly published security vulnerabilities (CVEs) and notify project managers of relevant risks
• Generate monthly SLA performance reports for client review meetings
• Maintain client documentation, runbooks, and meeting notes in Confluence
• Keep onboarding and operational documentation current as clients and environments change
• Support onboarding of new clients into managed services

Technical Service Delivery Manager

Data Scientist

• Own and oversee cross-workstream alignment, dependencies, and critical path across the full programme lifecycle.
• Define, own, and continuously evolve programme-level artefacts, governance, and reporting to support decision-making and assurance.
• Provide clear, insight-led executive reporting to senior client and Valtech leadership, highlighting risks, opportunities, and recommendations.
• Own programme assurance, including regular health assessments and proactive intervention.
• Shape and mobilise new initiatives and opportunities within the engagement.
• Identify and drive improvements to delivery models, team structures, and ways of working.
• Act as an escalation point for complex delivery, commercial, or stakeholder challenges.
• Ensure delivery outcomes align with strategic client goals and long-term account objectives.

Data Program Manager

Technical Program Manager

• Lead complex, cross-functional programs from planning through execution and delivery
• Partner with engineering and product leads to drive data-informed strategy and decision-making
• Define program goals, success metrics, and KPIs aligned with business objectives
• Act as a thought leader, influencing roadmap prioritization and long-term product direction
• Design and lead experimentation frameworks (e.g., A/B testing, incrementality testing, measurement strategies)
• Conduct or guide quantitative analysis of performance metrics to identify growth opportunities and risks
• Define data tracking strategies and instrumentation for new features and product initiatives
• Build and maintain centralized reporting frameworks and metric dashboards
• Manage program timelines, risks, dependencies, and delivery milestones across multiple workstreams
• Ensure strong alignment between engineering, product, data, and business stakeholders
• Drive structured communication, status reporting, and executive updates
• Proactively identify and resolve blockers, ensuring high-quality and timely delivery
• Review and challenge technical design and implementation plans, particularly within Google Cloud Platform (GCP)

Technical Program Manager, GCP

Backend Engineer

• Architect, implement, and maintain MongoDB Atlas and non‑Atlas environments, ensuring high availability, scalability, and security.
• Design and enforce resiliency and disaster recovery strategies, including backup, restore, and multi‑region failover.
• Optimize database performance and query execution to support application development teams throughout all SDLC phases.
• Develop and manage infrastructure‑as‑code solutions (Terraform, GitOps) for database provisioning and automation.
• Implement and refine observability and monitoring solutions using Dynatrace, CloudWatch, and MongoDB native telemetry.
• Manage access control, auditing, and encryption to meet enterprise security and compliance requirements.
• Collaborate closely with application, DevOps, and platform teams to continuously improve reliability, performance, and operational excellence.
• Lead incident response for database‑related issues, drive root cause analysis, and implement corrective and preventative measures.
• Mentor and guide technical teams, contributing to documentation, standards, and design reviews.

Platform Database Engineer, MongoDB

Database Engineer, MongoDB

Product Manager

• Embed inside a Forward Deployed Experience Pod, working shoulder-to-shoulder with the client to learn the real workflow before you redesign it.
• Own the workflow, KPIs, and alignment for your pod. Define success metrics with the executive sponsor at week one, then build until you hit them. Measure outcomes against KPIs, not features shipped.
• Redesign the human experience around AI, not the other way around.
• Break a complex business problem into composable, shippable work the pod can ship in days, not quarters. Production progress every day.
• Work in your client's stack alongside the Forward Deployed Engineer and Forward Deployed Experience Designer in your pod.
• Pair with the Valtech leadership and your client's executive sponsor(s) to clear the path in real time. Legal, compliance, architecture, risk, governance, internal politics.
• Govern, secure, and measure outcomes from day one. AI in production demands real attention to evals, guardrails, and human-in-the-loop design. You own the framework that proves the solution works and keeps working after the pod rolls off.
• Transfer ownership cleanly. By the end of the engagement, the domain expert is set up to run the solution long-term without the pod. Documentation, conventions, and the team rituals that sustain the change are part of what you ship.
• Surface the next opportunity from inside the work. Embedded pods see what's broken next before anyone else does. You bring that signal back, so the pod earns its way into the next problem rather than waiting for procurement.
• Contribute to the evolution of Valtech's FDE practice. Every pod is a learning loop. Share what works, what didn't, and the patterns that should harden into how we deploy across clients.

Forward Deployed Product Manager

• Define end-to-end solution architecture including content architecture, integration architecture, security architecture, and deployment architecture.
• Lead architecture workshops and technical discovery sessions with clients and project teams.
• Define architecture standards, governance models, and technical guardrails across multiple delivery teams.
• Design scalable, secure, and maintainable Liferay DXP solutions aligned with business and enterprise architecture requirements.
• Design integration strategies for enterprise platforms such as DAM, PIM, CRM, ERP, CDP, Search, Identity Providers, and Middleware solutions.
• Create and review high-quality architecture documentation, technical specifications, solution designs, and architecture diagrams aligned with architecture standards and best practices.
• Assess technical risks related to integrations, performance, scalability, security, and maintainability.
• Support project estimations, solution planning, technical proposals, and change requests.
• Provide technical leadership and mentorship to architects, developers, and project teams.
• Troubleshoot complex technical challenges and provide guidance on production and platform issues.
• Support pre-sales activities, RFP responses, technical estimations, and solution presentations.

Technical Architect

Business Analyst

• Support the creation and refinement of user stories, acceptance criteria, and backlog items.
• Help translate business needs into actionable product and technical requirements.
• Assist in maintaining a clear, prioritized backlog that reflects team goals.
• Assist in system configurations, in collaboration with Architects.
• Partner with cross functional collaborators to build shared understanding of requirements and priorities.
• Participate in discussions, workshops, and reviews to ensure alignment.
• Document decisions, open questions, and follow ups to keep stakeholders informed.
• Help prepare sprint materials including backlog reviews, refinement notes, and sprint planning assets.
• Clarify requirements during development and ensure work aligns to acceptance criteria.
• Participate in or attend UAT testing and validation activities before release.
• Contribute to updates, summaries, and progress reports for internal and external audiences.
• Maintain clear documentation to ensure traceability and transparency.
• Surface risks or blockers early and help drive resolution.
• Foster a learning culture by experimenting with new ways of working.
• Observe patterns in workflows or communication and suggest improvements.
• Seek out feedback and coaching to build product ownership skills.

Business Analyst – Temporary Contract

Consultant

• Partnering with technical consultants to translate business needs into data models
• Running cross-functional workshops
• Producing deliverables such as process maps, business requirements, user stories, and decision logs

PXM Delivery Consultant

SEO Marketing

• Own organic content performance
• Develop and execute a global SEO content strategy aligned to Valtech's positioning as The Experience Innovation Company
• Conduct keyword research and competitive analysis to identify content gaps and topic clusters across key verticals — retail, automotive, financial services, health and B2B
• Partner with regional marketing teams to ensure global strategy translates into locally relevant execution
• Create and commission content that ranks and resonates
• Brief and develop long-form content — thought leadership, guides, case study landing pages and pillar pages — with clear direction on search intent, structure and narrative angle
• Work with subject matter experts, practice leads and leadership to surface Valtech's most distinctive thinking
• Guard Valtech's brand voice across all content you commission: confident, optimistic and human — never jargon-heavy
• Drive continuous improvement
• Track and report on organic traffic, keyword rankings, content engagement and conversion performance
• Conduct regular content audits and prioritise a refresh backlog that maximises SEO impact
• Stay ahead of algorithm changes, AI-driven search trends and LLM-optimised content (LLMO) best practices
• Collaborate across the marketing ecosystem
• Embed SEO thinking into the content creation process alongside copywriters, designers and editors
• Work with the Martech, Demand Generation and Campaign teams to support the full funnel
• Partner with the web team to implement on-page SEO best practices — metadata, internal linking, structured data and page experience signals

Senior SEO Content Strategist

AI Engineer

• Design and build agentic AI systems that facilitate conversational workflows for seller enablement
• Develop a chat-based seller assistant that:
• Answers seller questions using enterprise data
• Provides insights on ordering, pricing, and customer behavior
• Generates pre-visit one-pagers to guide sales conversations
• Integrate large language models (e.g., Claude, ChatGPT) with internal data sources and APIs
• Apply prompt engineering, context engineering, and agent orchestration techniques to improve reliability and usefulness
• Build and evolve the platform using LangChain and LangGraph (initially in Python)
• Design persistence and data access layers using Mongo or other data stores
• Collaborate closely with product, analytics, and engineering partners to shape both technical direction and use cases
• Serve as a champion for modern AI coding assistant tools (e.g., Cursor) within the team
• Help define standards and best practices as this AI capability scales

• Analyze media audiences, channels, target audiences, and placement locations;
• Interpret media briefings;
• Develop and present strategic and tactical media plans;
• Lead the operational process of requesting and evaluating proposals from media outlets;
• Implement digital campaigns, monitoring and optimizing their performance;
• Oversee and track published creative assets;
• Monitor the entire post-campaign process, preparing and presenting reports according to campaign, investment, and timeframe;
• Track potential media balances, contracts, and financial flows;
• Issue and send PIs/Purchase Orders to media outlets;
• Provide information to account management to support development of negotiation strategies with suppliers;
• Identify and monitor media and market trends, as well as keep track of competitors' media strategies;
• Develop mechanisms to track campaign performance and measure success against established business KPIs.

Senior Digital Media Consultant

• Drive advanced analytics, causal reasoning, and AI-powered decision intelligence across multiple use cases
• Build production-grade systems that combine predictive, causal, and generative AI capabilities
• Turn complex data into actionable insights, automated decisions, and intelligent workflows
• Design and deploy systems that integrate experimentation, observational data, machine learning, and generative AI
• Collaborate closely with data engineers, ML engineers, analysts, and platform teams

Senior Data Scientist

• Drive advanced analytics, causal reasoning, and AI-powered decision intelligence across multiple use cases within our AI portfolio.
• Work at the intersection of data science, machine learning, and GenAI, turning complex data into actionable insights, automated decisions, and intelligent workflows.
• Design and deploy systems that integrate experimentation, observational data, machine learning, and generative AI into real-time or near-real-time decision-making pipelines.
• Collaborate closely with data engineers, ML engineers, analysts, and platform teams, contributing to shared modeling standards and cross-functional AI architecture.
• Develop and deploy machine learning models across use cases (forecasting, optimization, recommendation systems).
• Apply statistical, predictive, and prescriptive modeling techniques to solve business problems.
• Build reusable modeling frameworks that can scale across multiple domains.
• Design and implement causal inference methods (e.g., uplift modeling, experiments, quasi-experimental methods).
• Translate observational and experimental data into actionable business insights.
• Embed causal reasoning into decision systems that guide actions (e.g., optimization, prioritization, trade-offs).
• Integrate GenAI capabilities (e.g., LLMs, RAG pipelines, agent-based systems) into data science workflows.
• Contribute to the development of intelligent agents and AI-assisted decision-making systems.
• Combine structured data models with unstructured data and GenAI outputs.