AI Solutions Consultant

Opus AI Technologies is a pioneering AI company in Austin, Texas, and we are growing fast.

We build Opus, the agentic AI platform for regulated industries. Insurers, health systems, and financial institutions use it to see what their processes actually cost them, rebuild those processes with AI agents, and then run them at full speed with people still in the loop. Work that used to sit in an IT queue for weeks now takes minutes, and the business team does it themselves.

That only works because governance, auditability, and compliance are built into the platform rather than bolted on afterward to satisfy an auditor. It is why a compliance officer will sign off on what we deliver, and why enterprises trust Opus with the work they cannot afford to get wrong: the claim that decides whether a family gets covered, the loan file, the patient record, the benefits application with a person waiting on the other end.

The role

Solutions Consultants join after the sale and stay until the workflow is live. The work starts with separating the process a client describes from the one their systems and their regulators will actually permit, and it ends with a design their IT organization has approved and their operators will use.

You’ll work in a delivery squad with a Project Manager who owns the engagement and the schedule, AI Workflow Engineers who build, and a Business Analyst who captures current-state process detail. You’ll stay close enough to the build to defend your decisions when they meet reality.

What you’ll own

Technical discovery and architecture

Lead technical discovery and find the real constraints behind the stated requirements: data quality, system access, regulatory limits, latency, volume, and the organizational politics that determine what can actually change.

Define the target-state workflow architecture. Where agents act, where humans review, what the exception and escalation paths are, and how the whole thing is audited.

Define integration points across client systems (APIs, data sources, document repositories, identity, cloud infrastructure).

Set the success criteria and evaluation approach before the build starts: what the workflow has to get right, how accuracy will be judged, and what threshold constitutes done. Leaving this vague is the most common reason enterprise AI projects fail.

Business case

Build the business case that quantifies the impact of the deployment (cycle time, cost per transaction, error and rework rates, throughput) and make the assumptions behind it explicit enough to be challenged.

Hand the Project Manager the metrics that need baselining before go-live, and stand behind the numbers when the results come back.

Client relationship

Act as the trusted technical adviser to the client’s technical and business leadership, and build the internal advocates who will carry the project when you are not in the room.

Navigate the gap between IT and Operations, which usually want different things from the same deployment.

Run demonstrations that show the business result rather than the feature set.

Technical leadership

Give clear, actionable technical direction to both client teams and our Workflow Engineers.

Serve as the escalation point for complex technical problems during delivery.

Maintain design decision logs and interface definitions per engagement, and turn recurring architectural choices into solution patterns the next Consultant can start from.

What we’re looking for

Experience

5+ years in solutions consulting, technical consulting, solutions architecture, or technical business analysis.

Proven post-sales experience carrying enterprise clients through delivery, not just pre-sales.

Strong background in workflow automation, distributed systems, or AI/ML-driven platforms.

Experience in a regulated industry - financial services, insurance, healthcare, or government - is a strong plus.

Technical depth we value

Real fluency in how modern AI systems are built and evaluated: LLM capabilities and limits, prompting and agent patterns, retrieval, evaluation frameworks, guardrails, and where hallucination and drift show up in practice.

Able to discuss APIs, webhooks, data pipelines, and integration architecture credibly without pulling an engineer into every conversation.

Requirements engineering. You can turn a vague use case into a technical specification and sequence diagram an engineer can build from.

Working understanding of security and compliance constraints in enterprise deployments.

How you work

Executive presence. Comfortable challenging a C-suite assumption, and comfortable holding a design decision under pressure from people who outrank you.

Steady under scepticism, including the well-founded kind. You can tell the difference.

Fluent across audiences: client engineers, operations leads, and executives in the same week, in the right register for each.

Why this role

Direct influence on the Opus roadmap. What you learn in the field shapes what we build.

Joint delivery alongside consulting partners on engagements most vendors never get near.

A clear path toward principal architect or practice leadership as the US team grows.

Competitive compensation and founding-team leverage as we scale the US delivery practice out of Austin.

Logistics

Location: Austin, Texas preferred. Remote considered for exceptional US-based candidates.

Work authorization: Opus AI Technologies is not able to sponsor work visas for this role, including H-1B and OPT/CPT extensions requiring employer sponsorship. Candidates must already be authorized to work in the United States for any employer, without current or future sponsorship.

Equal opportunity: We’re building a team from a range of backgrounds and we evaluate candidates on what they can do. If you don’t match every line above but think you’d be good at this, please apply.