You are a fixed income market professional who grew up inside the “plumbing” of trading: first by selling and implementing institutional order/trade workflows (Bloomberg), then by operating and monetizing credit flow (Dallas VP roles), then by helping tier‑1 institutions deploy liquidity and signal platforms (Algomi). You are not “a finance guy who learned to code” in the shallow sense; you are someone who learned where the market’s friction lives, then repeatedly moved closer to the systems that create/resolve that friction.
The most important arc isn’t the job titles; it’s the transition from “domain expert who can explain the market” to “domain developer who can build and operate systems that reshape the market.” CatFIX was your explicit entrepreneurial expression of that arc. Katana became the forcing function that turned “interest in engineering” into “ownership-level engineering reality,” because cloud invoices do not negotiate: they either get paid, or the system dies.
Your differentiated value is the combination of (a) fixed income microstructure understanding, (b) client-facing trust building, and (c) a growing toolkit in modern cloud/data/ML engineering that you’re motivated to master because you’ve owned the consequences.
You completed your undergraduate degree at Texas Christian University (the source set includes differing date notations, but consistently places the late 1990s as the timeframe). What matters here is less the major and more the pattern: you didn’t start as a pure engineer; you started as a communicator and operator who would later specialize into systems.
Bloomberg is the foundational decade.
You weren’t merely “in sales.” You were in the transactional products/trading solutions ecosystem where the product is an operational reality: order management, trade workflows, straight‑through processing, integration, adoption, and the social engineering required to get institutions to change.
Key durable outcomes that show up repeatedly in the material:
You learned how to sell complex systems and how to land implementations at real firms. You learned the language of desk heads, ops teams, and technologists. You developed the mental model that markets become electronic one workflow at a time, and that adoption is driven by reducing friction and earning trust.
This phase also shaped your style: high-energy communication, persuasion, and an instinct for translating complicated concepts for diverse audiences.
You moved from implementation/sales into roles closer to trading P&L and flow. The Dallas VP roles (Southwest Securities, Tejas Securities, Esposito Securities) are the “operator years.”
Recurring signals from the content:
You were engaged in building and marketing electronic trading capabilities for credit, mixing voice and electronic, and using technology (including Bloomberg systems) as a lever for revenue and differentiation. You were not just executing; you were designing how a desk would operate: how it sources liquidity, how it interacts with clients, and how it scales beyond heroics.
This phase is where “market intuition” and “system thinking” start to fuse: your success depended on understanding both microstructure and the operational process around it.
Algomi deepened your platform exposure and made your work more explicitly about turning internal/private information into actionable signal and workflow.
Core elements that recur:
You worked across Europe implementing Synchronicity/Honeycomb and later ALFA-type workflows for tier‑1 sell‑side and buy‑side institutions. You designed bespoke algorithmic logic and helped desks move flow toward digital execution.
This is also where the material explicitly says you were exposed to the detailed application of FIX in fixed income contexts, which becomes important later for CatFIX and for how you talk about “plumbing” credibly.
CatFIX is your entrepreneurial translation of everything earlier.
From the sources, CatFIX is positioned as FIX protocol consulting and fixed income fintech marketing/product support for banks (often regional banks). More broadly, it’s a statement: you saw that institutions needed practical integration, workflow, and go-to-market help, and you built a vehicle to provide it.
The way CatFIX shows up in your materials also signals a preference: you don’t want to be purely advisory. You like building, shipping, and making systems real.
Katana is the hinge.
As an advisor/sales-and-awareness person, you were responsible for go-to-market, partnerships, and making the platform legible to a market that often distrusts black boxes.
The narrative becomes vivid around the acquisition:
Katana (spun out of ING, with valuations referenced in your narrative materials) faced liquidation and IP sale. You initially engaged via a modest bid to review financials, then negotiated and acquired the IP. You describe the first major cloud invoice as a turning point that forced you to pause other commitments and learn cloud cost control and platform operations deeply.
What matters here is not the exact valuation numbers; it’s the behavioral signature:
You were willing to take a calculated risk on an asset you understood in a way many would not. You committed personally to making it viable, and you converted financial pressure into a structured learning path.
Technically, the story asserts a platform that analyzes an enormous combinatorial space of bond pairs (hundreds of millions), uses distributed processing (Apache Beam/Dataflow patterns), and uses ML/neural nets to rank mean-reversion opportunities. You consistently describe the stack as spanning Go/Node/TypeScript/React/Python, PostgreSQL, GCP services, and a workflow that integrates into Bloomberg distribution.
Strategically, Katana becomes your “bridge”: it connects your market identity (fixed income signal generation) with your engineering identity (distributed systems, cloud cost discipline, and ML workflow literacy).
Phase G — Formal reskilling (2023–2025): turning “operator curiosity” into structured engineering depth
Multiple sources highlight UT Austin McCombs professional certificates, including cloud computing and full stack software development. This is consistent with your written identity as “domain expert to domain developer.”
The UT offer letter in the source set confirms admission to the full stack certificate (Jan 2024) and implies a deliberate, structured approach: you’re not relying on vibes; you’re building a curriculum around the gaps you discovered while operating Katana.
This phase also includes a visible meta-skill: narrative construction. You’re actively producing variants of your story for different audiences (website, Medium, X, tailored resumes, cover letters). You’re iterating the same core truth with different emphasis.
If I had to summarize “how you came to this point” without reducing it to bullet points: you repeatedly moved toward the constraint.
At Bloomberg, the constraint was institutional adoption: how do you land complex workflows in real firms?
In Dallas, the constraint was monetization and execution reality: how do you generate flow and revenue in credit markets using both voice and electronic tools?
At Algomi, the constraint was platform rollout and signal-to-workflow translation: how do you convert internal/private data into something that traders and PMs actually use?
At CatFIX, the constraint was entrepreneurship: can you build a services/product vehicle that solves specific institutional needs?
At Katana, the constraint was ownership: can you keep a complex cloud/ML platform alive and make it economically viable while learning the underlying architecture?
The result is a career that looks like “sales/trading/product/tech” on paper, but in reality is a coherent sequence of increasing responsibility for systems.
The skills lists in the source folder are large. What’s more revealing is the clustering: which skills reinforce each other, and what outcomes they enable.
Your finance skill lists consistently include: fixed income trading, credit, HY/IG/emerging markets, market microstructure, best execution/TCA, risk and analytics framing, and a wide familiarity with execution venues and workflows.
This matters because it gives your technical work “target selection.” You don’t build generic pipelines; you build pipelines that map to liquidity, risk, and execution.
Your behavioral profile is consistent across sources: high-energy communicator, socially fluent, persuasive rather than directive, fast-moving, and motivated by progress and opportunity.
The shadow side is also explicit: impatience with repetitive routines and details.
In practice, this implies your best operating mode is: you set direction, you communicate relentlessly, you build momentum, and you delegate or automate the grind.
Across the materials, the engineering/tool stack you identify includes:
Modern language fluency (Python, JavaScript/TypeScript, Node; plus interest/experience signals in Go).
Cloud platforms (GCP as the core, with awareness of AWS/Azure).
Distributed data processing patterns (Apache Beam; event-driven architectures; Pub/Sub/Kafka vocabulary).
Infrastructure-as-code and cost discipline (Terraform and “turn off what you don’t need” operational optimization).
A practical DevOps posture (CI/CD, containerization, observability).
What stands out is the combination of “operator constraints” with “engineer tools.” Many people learn these tools in a vacuum; you learned them because a production system demanded them.
The skill inventories and portfolio notes include agentic AI workflow design and prompt engineering as explicit skills, alongside root-cause analysis, rollback planning, and documentation discipline.
This aligns with your demonstrated preference for structured runbooks and “verify-first” operating.
The repeated emotional landmarks:
You get energy from inflection points: moving markets from voice to electronic, turning private data into signals, bringing systems to life in production.
You value ownership: acquiring IP, taking responsibility for costs and viability, and deciding to learn what you need to learn rather than outsourcing understanding.
You value communication as leverage: you repeatedly position yourself as a bridge between market participants and technology builders.
You are motivated by variety and pace: your behavioral profile explicitly says you become less effective under repetitive routine and details.
The “custom instructions” and portfolio notes paint a clear working philosophy:
You prefer simple, testable systems and you are sensitive to waste (time, money, cloud costs, operational friction).
You prefer tooling and workflows that reduce cognitive load (optimized CLI tools, repeatable environments, credential hygiene).
You are building toward a disciplined engineering practice (TDD emphasis shows up as a stated principle, as do package management rules like using uv).
You treat security and secrets handling as non-negotiable (multiple artifacts highlight 1Password/SSH key management and eliminating secrets from the filesystem).
Katana isn’t just a product; it’s the narrative proof that you can take ownership of complex, interdisciplinary technology.
It also shows a specific leadership style:
You’re willing to lead without pretending to be the original author of the system. You respect the expertise of the team that built it, but you take responsibility for operating it.
You invest in learning rather than hand-waving. The cloud invoice turning point is a concrete example of “pressure converts to curriculum.”
You build outward-facing narrative and distribution: Bloomberg integration, marketing assets, content production, and partnerships are treated as part of the system.
The source content frames you as someone intentionally pivoting into deeper technical leadership roles while retaining your market domain edge.
The resumes and cover letters indicate you are positioning for senior roles where that hybrid profile matters: electronic trading leadership, architecture, risk engineering/analytics—roles where you can set direction, translate between functions, and drive systems to production outcomes.
A fair articulation of your current “edge” is: you can talk to the desk, the CTO, and the data engineer without faking any of the worlds, and you’re increasingly able to build or oversee the actual systems.
High-signal narrative sources:
Profiles/ProfileonWebsite.md; Profiles/About Me.txt; Profiles/LLM_Context_John_Shelburne.md; Profile_Summary_08_2025; Profiles/Profile on Medium.txt; Profiles/Profile on X.txt; Profiles/ChatGPT_Custom_Instructions.md; whatdoiwant.md.
Resume variants / role positioning:
executive_director_resume_07_2025.md; director_resume_07_2025.md; vp_resume_07_2025.md; Letters/*.md.
Skill inventories:
Skills/master_skills_list.md; Skills/Capabilities_08_2025; Skills/finance_skills.txt; Skills/katana_skills.txt; Skills/priority_skills.txt; Skills/behavior.txt.
Portfolio/work-style evidence:
Portfolio/1passwordSSH.md; Portfolio/dotfilePromotion.md.
PDF fact checks (light extraction via pdftotext):
OCR bio/CV; UT Austin offer letter; employment agreements (dates/titles only).