Jobs at Saksham Test

Design, build, and maintain web applications and microservices using Go and React. Drive technical decisions, mentor engineers, improve CI/CD, testing (unit, integration, E2E) and observability, diagnose performance/security issues, and collaborate with product and design to deliver reliable, well-tested solutions.

Lead full-cycle recruiting for Go-to-Market roles (Sales, Customer Success, Solutions Engineering, etc.). Partner with hiring managers to design structured interviews, build talent pipelines, source candidates, negotiate offers, and support onboarding. Use recruiting metrics and market insights to drive hiring decisions and improve processes while promoting inclusive hiring practices.

Design, harden, deploy, and operate LLM-powered applications and agents on a governed GCP platform. Build integrations, retrieval pipelines, dashboards, monitoring, CI/CD, secrets management, and automated maintenance while partnering with business stakeholders to move proofs-of-concept into production.

Join the IT AI Automation team to build and harden micro-apps and AI integrations on a governed GCP platform. Contribute to bug fixes, small features, code and design reviews, apply foundational security and software practices, monitor applications, and use AI tools to support development, testing, and documentation while learning from senior engineers.

Lead intake, roadmap, and governance for an AI automation/platform team that hardens and ships business-built AI apps to production. Define security, MLOps, responsible-AI standards, evaluate vendor tooling, manage stakeholder communication, measure adoption and costs, and enable business units for safe, scalable AI deployments on a shared GCP platform.

Design, build, and optimize BigQuery-based data models and pipelines on Google Cloud. Implement SQL procedures, manage storage/partitioning, ensure data quality, collaborate with data scientists and engineers, document designs, and improve ETL and reporting workflows.

Lead and execute agency adoption and engagement strategy across Applied's commercial lines portfolio in North America. Build scalable operating models, drive executive-level agency relationships, orchestrate cross-functional teams, and convert product availability into sustained day-to-day usage and bound premium. Own major migrations, digital adoption motions, change management, and measurable market outcomes.

Lead portfolio-level strategy and operating cadence for Product and Engineering. Build prioritization frameworks, capacity and ROI models, reporting architecture, and drive cross-functional tradeoffs. Translate roadmap outcomes to the E-Team and Board and lead/coordinate critical cross-functional initiatives.

Lead a newly formed data engineering team to build and standardize data engineering best practices for AI-driven products. Drive cross-functional initiatives, provide hands-on guidance in SQL, data modeling, and the GCP data/streaming stack, champion AI-assisted engineering workflows, and balance technical leadership with people management.

Design, deploy, and operate enterprise network infrastructure across data centers and cloud (GCP, AWS, Azure). Manage hybrid connectivity, BGP, VPNs, F5 load balancers, and network observability. Build IaC and automation using Terraform, GitLab CI/CD, and Ansible. Create documentation and runbooks, collaborate with Cloud/Security teams, and participate in on-call rotations for incident response.

Support day-to-day Salesforce administration: gather requirements, configure platform (flows, fields, layouts, record types, automation), maintain data quality and security settings, triage support tickets, document processes, and collaborate with senior team members to deliver scalable user-focused solutions.

Serve as a technical pre-sales consultant for carrier customers: lead operational and technical discovery, map architectures and integrations, deliver demos and POCs, build sandbox configurations using APIs and scripting, respond to RFIs/RFPs, coordinate site visits, and support sales hand-offs to drive adoption and ROI.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-service analytics (Pendo, BigQuery, Tableau). Partner cross-functionally to translate user behavior into roadmap recommendations, embed measurement in product lifecycle, surface growth opportunities, and scale AI-powered analytics capabilities while reporting to Product Operations leadership.

Lead strategy and delivery of AI-powered, agentic features for a SaaS insurance product area. Drive roadmap, define success criteria, build business cases, collaborate with engineering and data science, run experiments, track KPIs, and mentor junior PMs to maximize adoption, ROI, and customer value.

Lead large-scale DevOps/SRE programs: prioritize and plan cross-functional work, map and manage complex dependencies, surface risks and status to leaders, drive resolution of blockers, run integrated planning and retrospectives, and improve program processes and communication.

Manage and qualify inbound leads, nurture prospects through early sales stages, act as primary contact to connect clients with Applied Systems solutions, maintain CRM, prioritize multiple leads, and develop toward Inside Sales with training and career advancement opportunities.

Serve as primary post-sale owner for strategic carrier and broker accounts: drive adoption and utilization of Cytora's AI platform, build senior relationships across underwriting, operations, and IT, run QBRs and executive reviews, identify renewal and expansion opportunities, coordinate cross-functionally, and travel up to 50% for onsite enablement.

Design and validate product experiences for EZLynx users: conduct user research and usability testing, create wireframes, mockups and prototypes, collaborate with product and engineering, use analytics to measure solutions and promote product consistency.

Lead enterprise data architecture, define large-scale warehouse/lakehouse and streaming platforms, set standards for data quality/governance/modeling, embed AI/agent workflows, build observability and incident-response for pipelines, mentor engineers, and influence cross-functional roadmaps.

Lead product analytics end-to-end: define metrics and measurement frameworks, analyze user behavior and product performance, build self-service dashboards, partner cross-functionally to link product outcomes to revenue, and translate data into strategic recommendations for product and GTM decisions.