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The Software Engineering Lead will design and maintain enterprise software applications, develop APIs, and build back-end systems, ensuring quality and best practices.

Design, build, and operate a multi-tenant, microservices-based platform on Kubernetes across cloud providers. Implement core platform components (Golang/Python), service mesh, observability, IaC, CI/CD, SLO-driven reliability, database and distributed-systems optimizations, incident response, and cost/performance tuning.

Owns a portfolio of strategic enterprise accounts end-to-end: accountable for delivery orchestration, post-go-live outcomes, executive stakeholder leadership, and commercial expansion. Staffs and directs delivery teams, ensures solution quality and ROI, runs QBRs, resolves escalations, translates customer needs into product feedback, and coaches teams to drive continuous improvement and scalable account practices.

Lead end-to-end delivery and stabilization of agentic AI solutions from design through production. Translate business workflows into feasible AI workflows, provide technical oversight, coordinate stakeholders, de-risk integrations and data issues, report progress and outcomes, and mentor delivery teams to ensure reliable, scalable production deployments.

Lead AI strategy for high-value enterprise accounts: advise C-level stakeholders, shape transformation roadmaps and business cases, influence deal strategy with executive leadership, structure engagements and proposals, run workshops and discovery sessions, and collaborate with product, engineering, GTM and delivery teams to align solutions and mentor internal teams on strategic storytelling and engagement design.

Lead full-cycle technical recruiting for engineering and product teams: intake, sourcing, screening, interview coordination, offers, and onboarding. Build proactive pipelines, run intake meetings, partner with hiring managers on scorecards and interview loops, improve hiring processes and metrics, maintain ATS hygiene, and ensure an excellent candidate experience while driving hiring velocity.

Design, build, and maintain scalable backend systems and APIs using Go/Python. Integrate enterprise services, data pipelines, event-driven tech (Temporal, Kafka), and LLMs (OpenAI, Gemini, Claude). Ensure security, high availability, multi-tenant SaaS deployments, and improve engineering practices across the stack.

The Product Manager will define product strategy, conduct market research, collaborate with teams to develop products, and ensure successful product launches while tracking performance and iterating based on feedback.

Lead social media and community strategy to scale Ema's brand and LinkedIn presence, create and repurpose content (blogs, carousels, short videos, newsletters), run experiments and performance tracking, build and engage a private enterprise AI community, support ABT microsite and events, and help convert community activity into sales pipeline.

The AI Implementation Engineer delivers and stabilizes AI solutions in customer environments, ensuring integrations and workflows meet requirements while coaching customer teams during critical phases.