Benefits:

• Massive Impact: The potential of enterprise AI is unbounded, and we're at the frontier.

• Real Technical Challenges: Design systems no one else has ever built in order to tackle problems that no one else has ever solved.

• Ownership That Matters: We trust our team members to direct influence on product direction and own entire systems.

• Elite Technical Team: Work with and learn from the best

Education Requirements:

• Strong engineering background, preferred in fields such as Computer Science, Software Engineering, Mathematics, Physics, or related technical disciplines

Experience Requirements:

• 2+ years of relevant, post-college work experience in software engineering, preferably in customer-facing or deployment roles

• Strong coding skills with proficiency in programming languages such as Python, TypeScript/JavaScript, Java, or similar

• Experience building production systems—APIs, data pipelines, web applications, or integrations with enterprise software

Other Requirements:

• Intellectual curiosity about AI/ML systems and their application to real-world problems

• Ability and interest to travel up to 25-50% as needed to customer sites for onboarding, training, and deployment (flexible based on customer needs and personal preferences)

• Experience with AI/ML systems, LLMs, or agent frameworks

• Prior work in consulting, professional services, or customer-facing technical roles

• Familiarity with enterprise software ecosystems (Google Workspace, Slack, Linear, etc.)

• Background in or curiosity about specific domains: telecommunications, finance, consulting, biotech, engineering systems

• Experience with cloud infrastructure (AWS, GCP, Azure) and modern DevOps practices

• Track record of driving measurable impact in customer deployments or product implementations

Responsibilities:

• Collaborating with engineers on architecture and design decisions for AI agents that execute complex workflows

• Wrangling massive-scale data—integrating codebases, operational systems, data rooms, and proprietary datasets into stable pipelines that ground AI in institutional intelligence

• Building custom AI workflows tailored to customer needs: engineering diagnostics, financial analysis, client deliverable generation, code shipping

• Developing integrations that connect Context agents to customer tools and systems—Slack, Linear, Google Workspace, proprietary platforms

• Engineering the learning flywheel—building systems that capture subject matter expert feedback and continuously improve AI agent capabilities

Benefits:

• Massive Impact: The potential of enterprise AI is unbounded, and we're at the frontier.

• Real Technical Challenges: Design systems no one else has ever built in order to tackle problems that no one else has ever solved.

• Ownership That Matters: We trust our team members to direct influence on product direction and own entire systems.

• Elite Technical Team: Work with and learn from the best

Education Requirements:

• Technical background—CS degree, prior engineering experience, or deep technical expertise that helps you engage with customer engineering teams

Experience Requirements:

• 3+ years of Technical Account Management, Customer Success, or Solutions Engineering experience managing strategic enterprise accounts (Fortune 500 companies)

• Proven track record of driving customer retention, expansion, and executive relationships—ideally with net revenue retention metrics >120%

• Technical depth—comfort discussing AI/ML systems, APIs, data integration, enterprise software architectures, and troubleshooting technical issues

• Experience with complex, technical products—ideally AI/ML platforms, developer tools, data infrastructure, or enterprise software

• Strong business acumen—ability to articulate ROI, measure business impact, and present outcomes to executive stakeholders

Other Requirements:

• Executive relationship management—demonstrated ability to build trust with C-suite, VPs, and senior leaders

• Consultative approach—curiosity to understand customer workflows deeply and identify opportunities for expansion

• Excellent communication skills—equally comfortable writing technical documentation and presenting business reviews to executives

• Experience with AI/ML, LLMs, or agent frameworks—understanding of how AI systems work and what makes deployments successful

• Prior work in consulting, professional services, or customer-facing technical roles—you've been in customers' shoes

• Familiarity with specific verticals—telecommunications, finance, consulting, biotech, engineering systems

• Experience managing high-touch, strategic accounts with >$1M ACV

• Track record of driving expansion and upsell within existing accounts

• Customer advocacy and storytelling skills—experience creating case studies, references, and customer-led content

• Proficiency with customer success platforms—Gainsight, Totango, ChurnZero, or similar tools

Responsibilities:

• Own customer relationships for a portfolio of strategic enterprise accounts—serve as primary point of contact and trusted advisor for executives, engineering leaders, and operational teams

• Drive customer success and adoption—ensure customers successfully deploy Context AI agents, achieve measurable business outcomes, and expand usage across workflows and teams

• Conduct executive business reviews—present quarterly and annual reviews to C-suite stakeholders showcasing productivity gains, cycle time reductions, ROI, and strategic roadmap alignment

• Monitor customer health and proactively address risks—track adoption metrics, usage patterns, and satisfaction signals to identify and mitigate churn risks before they escalate

• Identify expansion opportunities—discover new use cases, departments, and workflows where Context can deliver value; partner with Sales to drive upsell and cross-sell motions