Forward Deployed Engineer

Cogniify • Austin, TX

128d • $150,000 - $190,000 • Remote

About The Position

At Cogniify, we believe AI should move beyond pilots and prototypes into real, governed, enterprise-scale production. We partner with Fortune 100 and global enterprises to advance AI from readiness through to production — with the governance, financial discipline, and operational rigor that large organizations require. Our work is anchored in the 4S Intelligence framework — Sharper Analytics, Smarter AI, Scalable Systems, and Secured Governance — and spans strategy, engineering, and AI delivered as end-to-end ecosystems, not siloed projects. We don't sell a one-size-fits-all platform — every engagement is a custom-built solution designed around a client's specific problem, data, and constraints. Our philosophy is simple: clarity, trust, and measurable outcomes.

Requirements

• 9–12+ years of overall technology experience, including significant time in architect-level or technical lead roles on complex, enterprise-grade systems.
• Strong business acumen — genuinely curious about how a client's business works, able to get past the surface-level ask to the real underlying problem before jumping to a solution.
• Exceptional problem-solving ability — comfortable with ambiguity, able to structure an open-ended or poorly defined problem and independently arrive at a workable, well-reasoned solution.
• Demonstrated experience owning solutions end-to-end — from client conversation to architecture to hands-on build to executive presentation — not just one slice of the lifecycle.
• Strong, current hands-on proficiency in Python and SQL, with a track record of building production-quality data pipelines, APIs, and applications personally (not just directing others).
• Deep experience with modern data platforms (Snowflake, Databricks, BigQuery, or Redshift) and orchestration tools (dbt, Airflow, Dagster, or Prefect).
• Strong grounding in AI/GenAI application patterns: LLM integration, RAG pipelines, embeddings, vector databases, and agentic workflows using frameworks such as LangChain or LlamaIndex.
• Working knowledge of at least one major cloud platform (AWS, Azure, or GCP), including compute, storage, networking, and managed AI/data services.
• Proven ability to engage directly with C-level and senior executive stakeholders — framing ambiguous problems, facilitating prioritization discussions, and presenting technical solutions in business terms.
• Strong stakeholder management skills — able to manage competing priorities across client, investor, and internal audiences, and build trust quickly in new environments.
• Prior experience in client-facing consulting, pre-sales engineering, solutions architecture, or a founding/lead engineering role at a fast-moving company.
• Comfort with rapid context-switching across unfamiliar codebases, domains, and technology stacks under tight delivery timelines.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).

Nice To Haves

• Experience with MCP (Model Context Protocol) or similar tool-layer/agent-integration patterns.
• Experience building client-facing applications, dashboards, or internal tools using React, Next.js, or low-code platforms (Retool, Appsmith).
• Experience with containerization and infrastructure-as-code (Docker, Kubernetes, Terraform) for deployment automation.
• Familiarity with data quality and observability tooling (Great Expectations, Monte Carlo, dbt tests, or Soda).
• Prior experience working with private equity portfolio companies, or in transformation programs tied to investor/board reporting cycles.
• Domain experience in financial services, healthcare, SaaS, or enterprise operations.

Responsibilities

• Own client engagements end to end — from discovery and opportunity framing through architecture, hands-on build, demonstration, and handover to execution teams.
• Lead discovery and working sessions directly with client CXOs, engineering leaders, and investor/board-level stakeholders to understand their business, uncover the real problem behind the stated ask, and frame the case for AI transformation.
• Assess a client's existing systems, data landscape, AI maturity, and engineering constraints, and translate ambiguous, often messy business problems into clearly scoped technical solutions.
• Architect and personally build production-credible, client-specific Proofs of Acceleration — including data pipelines, integrations, and AI/LLM-powered applications — within tight (2–3 week) delivery windows.
• Design and implement AI/ML-powered features such as RAG pipelines, LLM-based workflows, document processing, search/retrieval systems, and agentic or conversational AI, tailored to each client's environment.
• Integrate diverse enterprise data sources and systems: relational databases, data warehouses, REST/GraphQL APIs, event streams, SaaS platforms (Salesforce, Workday, SAP, etc.), and unstructured data.
• Deploy solutions on client cloud infrastructure (AWS, Azure, or GCP), ensuring security, scalability, and operational readiness even at prototype stage.
• Build the business narrative behind each PoA — quantifying ROI and connecting the technical solution to outcomes executives care about (cost, speed, revenue, risk).
• Present and defend solution designs live in front of technical and executive audiences, handling scrutiny and pushback in real time.
• Own stakeholder management across concurrent relationships — technical teams, business sponsors, and investor-side stakeholders — balancing competing priorities with confidence.
• Partner with account and engagement leadership to convert successful PoAs into full-scale Cogniify execution engagements, and produce handover documentation for delivery teams.
• Mentor junior FDEs and contribute reusable frameworks, accelerators, and playbooks that speed up future engagements.
• Operate as a mobile, high-trust resource — moving from one client engagement to the next as PoAs conclude.

Benefits

• Unlimited PTO.
• Very generous parental leave, much above industry standards!
• Entrepreneurial culture where pushing limits and taking risks is everyday business.
• Open communication with management and company leadership.
• Small, dynamic teams = massive impact.
• Medical, Dental and Vision coverage for employees.
• Access to Disability & Life insurance.
• Mental health and wellbeing support.
• Annual bonus program.
• Employer Stock Purchase Program (ESPP).
• Yearly team building experiences.
• Mentorship and sponsorship opportunities.
• Manager resources and support.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal