Wisedocs is a fast-growing, venture-backed AI platform that transforms how insurance companies analyze claims. With ~$20M USD raised, 100+ team members globally, and 90+ customers across North America and Australia, we’re doubling revenue year over year.   Founded by experts who’ve experienced the claims process firsthand, Wisedocs combines deep domain knowledge with next-gen AI trained on 100M+ documents. Our platform turns complex medical records into clear, structured insights—backed by expert human oversight.   Join a mission-driven team building intelligent products that cut through complexity, accelerate decision-making, and make a real impact when it matters most.    This is a remote role with twice-yearly on-site presence required in Downtown Toronto. Role Summary    We are looking for a Senior Solutions Engineer to partner with customers, Sales, Product, and Services to design and deliver effective solutions for complex enterprise use cases.  As we move upmarket, customer problems are increasingly nuanced and don't always map directly to existing product capabilities. In this role, you will be responsible for designing practical, high-impact solutions that balance what exists today with what is possible — playing a key part in ensuring Wisedocs can meet complex customer needs while remaining scalable to deliver.  This is a hands-on, collaborative role that combines solution design, customer engagement, and cross-functional alignment to ensure successful outcomes. If you enjoy solving real-world problems, working across teams, and turning ambiguity into clear solutions, we'd love to hear from you.  What you'll be doing   Solution Design & Execution  - Lead discovery to understand customer workflows, constraints, and goals  - Design clear, practical solution approaches that leverage Wisedocs’ capabilities  - Structure ambiguous problems into actionable solution plans  - Ensure proposed solutions are both valuable to the customer and feasible to deliver  Customer Engagement  - Lead solution-oriented demos, workshops, and proof-of-concept engagements  - Help customers understand how Wisedocs fits into their workflows and drives outcomes  - Build credibility through a strong understanding of customer needs and use cases  Product Collaboration  - Partner with Product to share grounded, actionable insights from customer engagements  - Help identify patterns in enterprise use cases that inform roadmap decisions  - Collaborate on shaping solutions where product capabilities are evolving  Scoping & Delivery Alignment  - Work closely with Customer Success/Services to scope implementations  - Ensure alignment between solution design and delivery approach  - Identify and communicate risks, dependencies, and constraints early  Internal Enablement  - Contribute to solution playbooks and reusable patterns for common use cases  - Support Sales and CS with guidance on positioning and solution approaches  - Share insights that improve how Wisedocs sells and delivers solutions  What Impact You Will Make  - Strengthen relationships with Wisedocs’ largest insurance carriers through proactive engagement, thoughtful business reviews, and consistent follow-through  - Drive retention and renewal outcomes by helping customers clearly understand and realize value within their claims workflows  - Reduce operational friction and escalations through early risk identification and structured intervention  - Influence product direction by bringing forward clear, customer-informed insights from complex carrier environments What Experience We Need  - 5+ years of experience as a Solutions Engineer or Sales Engineer in an enterprise SaaS environment  - Experience in regulated industries such as healthcare, insurance, or legal  - Strong solution design and problem-solving skills  - Technical aptitude, including understanding of integrations, APIs, and system workflows  - Experience working cross-functionally with Sales, Product, and Customer Success teams  - Ability to communicate complex concepts clearly to diverse audiences  - Experience working with AI tools, workflows, or prompting techniques  Nice to haves  - Familiarity with medical documentation or claims workflows  - Experience working with insurance carriers or disability claims What We Offer  - Remote work environment with opportunities to visit our Toronto HQ. - Modern employee benefits, including health and dental coverage   - Competitive compensation, with valuable stock options, as we’re still a young company growing very quickly.    - An opportunity to develop very rapidly in your career. We can offer you a super-immersive learning environment, and when you thrive there, you will have the opportunity to rapidly develop this opportunity into senior practitioner or management opportunities as you choose.    - Access to a learning and professional development fund to help you level up your career while you’re working with us. We hope to be an incredible step up in your career if you decide to come and work with us.    - Company events    - Generous Paid Time Off    - Paid Sick Days    - Casual Dress code    - Employee Referral Bonus    - Tuition Assistance    - Plus, many other Recognition Programs!    Recruitment Journey at Wisedocs    We're excited to meet you and explore the possibilities together!  At Wisedocs, honesty is one of our core values. Our Recruitment process is transparent to ensure you are set up for success:      - Round 1 – People & Culture Chat: 20–30 min conversation about your background, goals, and the role.   - Round 2 –  Interview with the Hiring Manager: Dive deeper into your background and experience, discuss the role in more detail, and get to know the team's vision and goals (45 min) - Round 3 – Case Study and Team Interview: You'll work through a case study that reflects the type of work you'd be doing in the role, followed by a conversation with key members of the team to assess overall fit and collaboration style (60 min) - Round 4 - Leadership Conversation: Meet our COO to learn about the Wisedocs vision and your impact (30 min)  Note: We’re embracing the possibilities of AI to work smarter, improve our systems, and create even better experiences for both our customers and our team. As part of this approach, we’re committed to building an inclusive and thoughtful hiring process and may use AI-powered tools to support parts of our screening and assessment process. These tools are used alongside human review to help keep our process fair, consistent, and efficient.  This posting is for current and future opportunities at Wisedocs. Even if there isn’t an immediate opening, we’re always excited to meet great people. If your experience lines up, we encourage you to apply — we’ll reach out when a role opens up that’s a good fit.  *Wisedocs AI is an equal opportunity employer and are committed to providing employment accommodation in accordance with AODA. If you require an accommodation, please notify us and we will work with you to meet your needs.

• Own the technical evaluation components of the sales process for accounts across your assigned territory. • Partner closely with Account Executives to drive technical strategy from first meeting through close and expansion. • Interface with the technical decision makers or influencers in key accounts: VP Engineering, CTO, platform engineering, architecture, DevEx, AppSec, and developers. • Understand how customers build software today: their architecture, SDLC, developer workflows, governance requirements, and what would need to be true for AI to be trusted in their environment. • Articulate the various Tabnine deployment options: SaaS, VPC (AWS, GCP, Azure), on-prem, and fully air-gapped deployments. • Run live demos and POVs that show how the Enterprise Context Engine helps AI tools understand system boundaries, dependencies, architectural patterns, code review signals, and organizational memory, not just the file in front of them. • Define and execute a scalable POV program with clear success criteria tied to things buyers actually care about: first-pass acceptance, review cycles, rework, time to resolution, and policy/compliance coverage. • Help customers understand how Tabnine can improve the tools they already use, instead of forcing a rip-and-replace story. • Track and provide feedback to Product and Engineering on customer usage patterns, deployment blockers, feature requests, and competitive intelligence.

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. About the Team The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. About the Role The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. What You’ll Do - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes What You’ll Bring - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos Nice to Have’s: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation & Benefits We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Annual OTE range: $150,000–$250,000 USD

About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. About the Team The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. About the Role The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. What You’ll Do - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes What You’ll Bring - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos Nice to Have’s: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints Compensation & Benefits We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Annual OTE range: $150,000–$250,000 USD