futureproof consulting

• Lead technical architecture for large-scale Agentic AI platforms • Define scalable cloud-native solution architecture • Own architecture decisions across multiple engineering teams • Review designs, code quality and implementation approaches • Mentor architects and senior engineers • Lead implementation of enterprise Agentic AI solutions • Design production-grade architectures on AWS • Ensure solutions meet enterprise requirements for: RBAC, Authentication, Authorization, SSO, Encryption, Audit logging, Compliance • Work closely with DevOps teams around: CI/CD, Infrastructure as Code, Docker, Containerization, Cloud deployments

• Manage, optimize, and troubleshoot Nextflow pipelines for large-scale multi-omics workloads • Build and maintain CI/CD pipelines (Jenkins) for cloud infrastructure and scientific workflow deployments • Develop and maintain Infrastructure as Code (Terraform, Ansible, CloudFormation) • Design and integrate AWS services like EC2, S3, ECS, Batch, RDS, KMS into production environments • Ensure security, compliance, auditing, and reproducibility of scientific compute workloads • Support and optimize high-performance computing jobs spanning on-prem HPC clusters and AWS • Improve the reliability and throughput of analytical workflows processing petabytes of data • Collaborate with researchers to translate scientific needs into robust engineering solutions • Contribute to the design of microservices enabling scientific data exploration and visualization • Help build distributed systems supporting FAIR data principles • Partner with cross-functional teams to solve complex engineering problems end-to-end

• Design, develop, and maintain Celonis applications and solutions • Build and customize dashboards, analyses, KPIs, and process monitoring tools • Develop front-end components using Celonis Studio and related technologies • Implement back-end logic, data models, transformations, and integrations • Connect and integrate data from multiple source systems • Collaborate with business stakeholders, process experts, and technical teams • Support process mining and process improvement initiatives within the insurance domain • Troubleshoot, optimize, and enhance existing Celonis implementations

• Design and develop scalable ETL/ELT pipelines and data workflows • Build and optimize data models for analytics and reporting • Implement automation for data pipelines using CI/CD practices • Monitor data jobs and troubleshoot failures or performance issues • Support data consumption for: BI dashboards and reporting tools Data science and advanced analytics teams APIs and custom business applications • Work with structured and semi-structured datasets (CSV, JSON, Parquet, etc.) • Collaborate with cross-functional teams to deliver scalable data solutions

• Design, develop, and maintain full stack web applications • Build responsive and user-friendly frontend interfaces • Develop backend services and APIs supporting business workflows and integrations • Collaborate with architects, analysts, and other engineering teams • Ensure application performance, scalability, and security • Participate in code reviews and technical improvements

• Design and develop scalable, reliable data pipelines and infrastructure • Build ETL/ELT workflows for large-scale data processing • Develop and maintain data warehousing solutions • Process and analyze large datasets to support business insights • Ensure data integrity, quality, and governance standards • Optimize data collection, storage, and processing performance • Create dashboards, templates, and visualizations for stakeholders • Collaborate with business and technical teams to identify data needs • Design and execute experiments to validate data-driven solutions

• Lead reliability initiatives across production platforms and services • Define and manage SLOs, SLIs, SLAs, error budgets, and availability targets • Design and implement scalable, resilient cloud-native architectures • Automate infrastructure and deployments using IaC and CI/CD best practices • Build and maintain monitoring, logging, tracing, and alerting solutions • Drive incident management, troubleshooting, root cause analysis, and postmortems • Improve operational maturity through automation, runbooks, and best practices • Mentor engineers and support knowledge sharing across teams • Collaborate with product, security, platform, and vendor teams globally • Perform capacity planning, performance optimization, and reliability analysis • Maintain technical documentation and compliance-related artifacts where required

• Lead and support the technical design of conversational AI and contact center automation solutions (e.g., Cognigy.AI, Kore.ai, telephony integrations , or similar platforms). • Act as the technical liaison between developers, architects, and business teams — ensuring alignment across design, delivery, and performance goals. • Manage and refine the product backlog , translating complex business needs into actionable user stories. • Evaluate new AI and RAG technologies to improve conversational experiences and agent productivity. • Drive knowledge sharing and best practices across the team. • Organize and lead cross-functional meetings , fostering collaboration and innovation. • Prioritize requests effectively while maintaining clear visibility of deliverables and timelines.

• Lead and ensure timely completion of data cleansing activities • Manage data collection for manual and constructed objects • Collaborate with IT teams to define and implement value mappings • Create and maintain master data lists for assigned objects • Provide business insights for data extraction and transformation from legacy systems • Define and align data migration scope with country stakeholders • Ensure data readiness and quality throughout the migration lifecycle • Validate that data is fit for purpose and aligned with stakeholder requirements • Review and formally approve data upload files before and after loading • Perform manual data loads where required • Support dual maintenance activities • Execute and approve data validation scripts • Act as SPoC during defect management and hypercare phase

• Act as the primary Armis SME for laboratory environments • Configure, tune, and maintain Armis policies, alerts, and device classifications • Improve risk scoring models and detection logic to reduce false positives • Maintain accurate inventory of lab/OT/IoT devices • Collaborate on risk mitigation and remediation strategies • Define and maintain security policies and SOPs for lab environments • Configure and manage alerts for anomalies and threats • Investigate and triage incidents using Armis and related tools • Support incident response activities , including containment and recovery • Work closely with scientists and lab teams to align security with workflows • Deliver training and awareness sessions on secure usage of lab devices