Vetted Stakeholder Communication Professionals

“Backend/data engineer with experience on large-scale consumer platforms (Google and Meta), building high-traffic Python microservices (REST/gRPC) on Kubernetes with strong reliability/observability practices. Delivered AWS container-based deployments with CI/CD and IaC, and built AWS Glue ETL pipelines on S3 with schema evolution and data quality controls; also has demonstrated SQL tuning impact (15% latency reduction) and incident ownership for batch pipelines.”

“Senior engineering/technology leader who has defined and delivered a multi-year roadmap to modernize platforms and embed AI, leading global teams through cloud-native and microservices migrations on AWS/Azure. Demonstrated measurable outcomes including 99.99% uptime, 40% fewer incidents, 25% faster delivery, 5x scalability, and $30M in new business opportunities, while scaling a 100+ person distributed org with strong OKR-driven execution and mentorship culture.”

“Recruiting leader with experience at Google and YieldStreet who combines people management with a heavy personal requisition load (15–20). Partnered directly with HRBPs and the CFO on international/executive hiring, budgeting, equity decisions, and board-level quarterly planning. Led a department-wide ATS replacement and enforced interview training/compliance and SLAs to improve data quality and time-to-fill.”

“Engineering/tech leader with experience spanning major platforms (mentions Microsoft and AWS) and leading ML-driven product architecture (ranking systems). Describes driving a shift to a layered, API-standardized service architecture (including vector database components) that materially increased delivery speed (weeks to hours) while improving scalability and security, and emphasizes rigorous execution reviews (QDR/OKRs) plus transparent remote-team operating rhythms.”

“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”

“Engineering leader who built and scaled a distributed team (Serbia + US) to deliver an internal multi-tenant Kubernetes-based PaaS, moving a large org from manual ops-driven deployments to automated CI/CD with >99.97% uptime and 100% service adoption. Known for culture change (blameless post-mortems, clear intake via ticketing) and security-first platform practices (tenant isolation, Falco) supporting SOC2 compliance; also operates at exec level with stakeholder communication and fundraising.”

“Platform/backend engineer focused on Kubernetes at scale: built a Java control-plane service for multi-region cluster provisioning/monitoring/upgrades using Kafka-driven async workers, and solved peak-load provisioning failures by eliminating blocking I/O and dynamically scaling consumers. Also shipped an LLM-assisted Kubernetes troubleshooting/remediation feature that pulls Prometheus logs/metrics into prompts and uses guardrails (confidence thresholds + human-in-the-loop) to prevent risky actions.”

“Technology/architecture leader with Accenture experience delivering data- and AI/ML-driven products, including a legal contract search solution and customer sales analytics for AWS. Known for scaling distributed teams (onshore/offshore), making pragmatic architecture decisions, and solving hard data problems (proprietary sources, data quality) while implementing scalable integrations like Redshift-to-Salesforce via parallelized pipelines.”

“Engineering leader and former CTO/Disney|ABC engineering manager who built white-label mobile app architecture that supported a branded app and successful exit, and later scaled Disney Channel brand app teams across iOS/Android/web and major OTT platforms. Led kid-safety architecture for DisneyNOW (“Junior mode” with PIN) and partnered with product/legal on COPPA compliance, emphasizing maintainable tech choices and strong execution processes.”

“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”

“Engineering/technology leader with payments (UPI) scale experience who built fraud and growth systems for tens of millions of daily transactions while keeping CAC and cost guardrails. Scaled an engineering org from 12 to 155 in a year using platform + pod structures, and institutionalized canary deployments with auto-rollback (cutting degradations ~75%) while leveraging GenAI for code and test automation.”

“Engineering leader (ActiveCampaign, Yalo) with a track record of scaling both systems and orgs: grew an engineering team from 90+ to 200+ (30+ scrum teams) while re-architecting a marketing automation platform from batch to near real-time. Led major infrastructure shifts (RabbitMQ to Kafka, multi-region redundancy) and reports outcomes including 600%+ throughput gains, 99.99% uptime, and business growth from ~80K to 185K customers with revenue surpassing $200M over ~3 years.”

“Engineering leader with hands-on Android architecture expertise who has scaled mobile teams at Weedmaps (including forming a Platform team and rolling out MVVM/unit testing) and also co-founded a bootstrapped side business (Sizzle), owning the technical roadmap, hiring strategy (university pipeline + senior remote engineers in Pakistan), and stepping into fundraising when runway became critical.”

“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”