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About the Role

Bland AI is seeking Solutions Engineers to support growing enterprise demand. This hands-on role focuses on technical discovery, demo execution, POV scoping, and technical evaluation to help win enterprise deals by proving value quickly and credibly. You will partner closely with AEs, FDEs, Product, and Engineering.

Responsibilities

• Lead technical discovery with prospective customers to understand call center workflows, existing systems, integration requirements, operational pain, and AI readiness.
• Identify where Bland can deliver the clearest ROI and where the platform is best positioned to win.
• Qualify technical fit early so the team invests time in the right opportunities.
• Surface Bland’s technical differentiators naturally in discovery, especially around reliability, latency, security, governance, and customization.
• Work closely with AEs to define the technical win strategy for each opportunity.
• Design and run demos that map directly to a customer’s workflows, not generic product walkthroughs.
• Scope POVs around clear success criteria, timelines, milestones, and stakeholder expectations.
• Configure custom voice agent demos and technical proof points that show how Bland handles real-world complexity.
• Keep POVs focused and commercially relevant, avoiding unnecessary scope creep or “science projects.”
• Partner with FDEs and Engineering when deeper technical resources are needed, while protecting their time and keeping the sales process efficient.
• Drive urgency throughout the evaluation process by clearly defining next steps, owners, and decision points.
• Act as a credible technical voice in front of technical buyers, operators, InfoSec teams, procurement, and executive stakeholders.
• Explain Bland’s architecture, in-house voice stack, integration approach, and data/security posture in a clear and commercially relevant way.
• Support prospects through RFIs, security questionnaires, technical due diligence, and enterprise procurement processes.
• Build trust with skeptical buyers by being direct, knowledgeable, and honest about both Bland’s strengths and current limitations.
• Help customers understand what is possible today, what requires additional configuration, and what is not the right fit.
• Partner closely with AEs on discovery, win plans, POV strategy, and deal execution.
• Collaborate with FDEs on handoff, resource planning, technical feasibility, and implementation readiness.
• Feed product gaps, competitive learnings, customer feedback, and recurring technical objections back to Product and Engineering.
• Contribute to demo assets, POV templates, technical documentation, and repeatable pre-sales materials as the motion matures.
• Help define what “great” looks like for Solutions Engineering at Bland as the team scales.

Requirements

• 4–8+ years of Solutions Engineering, Sales Engineering, or technical pre-sales experience at a B2B SaaS company.
• Experience running technical discovery and supporting enterprise sales cycles.
• Owned or meaningfully contributed to technical POVs, POCs, pilots, or evaluations.
• Strong understanding of how to define POV success criteria, manage scope, and keep technical evaluations on track.
• Technical enough to configure demos, understand APIs, work with prompts, reason through integrations, and engage credibly with customer engineering or IT teams.
• Commercially strong enough to partner closely with AEs and understand how technical work ties back to deal progression.
• Comfortable operating in ambiguity at an early-stage or high-growth company.
• Genuine interest in AI, LLMs, voice automation, and enterprise workflow transformation.
• Background at a horizontal platform, developer infrastructure, API, automation, or workflow company.
• Experience with voice AI, conversational AI, CPaaS, CCaaS, contact center technology, or customer support automation.
• Experience selling into regulated or operationally complex industries such as healthcare, financial services, insurance, logistics, or enterprise support.
• Helped build or improve demo environments, POV frameworks, SE playbooks, or technical evaluation processes.
• Startup experience where the pre-sales motion was still being defined.

Skills

• Solutions Engineering
• Sales Engineering
• Technical Pre-Sales
• B2B SaaS
• Technical Discovery
• Enterprise Sales Cycles
• Technical POVs
• POCs
• Pilots
• Technical Evaluations
• Demo Configuration
• APIs
• Prompts
• Integrations
• Customer Engineering
• IT Teams
• AI
• LLMs
• Voice Automation
• Enterprise Workflow Transformation
• Horizontal Platform
• Developer Infrastructure
• API
• Automation
• Workflow
• Voice AI
• Conversational AI
• CPaaS
• CCaaS
• Contact Center Technology
• Customer Support Automation
• Regulated Industries
• Healthcare
• Financial Services
• Insurance
• Logistics
• Enterprise Support
• Demo Environments
• POV Frameworks
• SE Playbooks
• Technical Evaluation Processes

Location

• San Francisco
• Remote

Work Type

• 3–5 days in office
• Remote

Experience Level

• Individual Contributor

Benefits

• Full benefits package

About the Company

• Bland AI is the enterprise voice AI platform built for organizations with high-volume, complex customer conversations.
• Founded by Sobhan Nejad and Isaiah Granet in San Francisco, Bland built its own voice models and infrastructure from the ground up to solve the latency, reliability, and control challenges that have historically limited enterprise adoption of voice AI.
• Today, Bland powers more than 3.5 million calls per week across regulated industries and has raised over $100M to accelerate its mission of building the most secure enterprise platform for high-stakes customer interactions.
• Bland's platform fully resolves up to 65% of inbound calls autonomously—handling not just FAQs, but multi-step workflows, authentication, business-rule-based routing, and live data lookups.
• For large contact centers, every additional percentage point of autonomous resolution can translate to $500K–$1M+ in annual savings, making the ROI story unusually compelling.
• Bland's biggest technical differentiator is that it owns and operates the entire voice stack in-house—speech recognition, orchestration, and text-to-speech—rather than stitching together third-party APIs.
• This architectural approach gives enterprise customers greater reliability, security, governance, and customization, particularly in highly regulated industries.
• The company is scaling rapidly, with ~$30M ARR, 4× YoY growth, and 140%+ NRR.
• Bland now serves 250+ enterprise customers and processes more than 175 million AI phone calls annually.