Resume · Quant engineering

John Kingola @Astralchemist

Quant engineer · Strategy parameters, entry filters, and backtesting infrastructure · Rust and Python

I check that something is true before anyone relies on it: trading strategies, AI agents, and the systems around them.

  • Nairobi, Kenya (UTC+3)
  • remote as a contractor or through an EOR
  • no visa sponsorship needed

I design the parameters and filters that decide when a trading system acts, and build the infrastructure that shows whether the result is real. In Cernos I ported LEAN's indicator library to Rust (241 indicator types) inside a research engine that translates strategies from eight languages into one portable format, counts every parameter trial against overfitting, and exports the winner as standalone Python or C++. I rebuilt published FX and gold systems from their trade logs, tuning filters on one half of the data and judging them on the other. I have done this for six years, since 2020, from MQL5 Expert Advisors built to client risk specifications to a backtest-as-a-service API with a cache keyed on the strategy hash. Currently technical advisor on algorithmic systems for a trading startup, and lead engineer behind the Change Intelligence Platform, which I built end to end and now maintain.

Download PDFgithub.com/AstralchemistLinkedIn[email protected]All resumes
trading systems, since 2020
6 yrs
trading systems, since 2020
LEAN indicator types ported to Rust
241
LEAN indicator types ported to Rust
upstream fixes merged and credited
5
upstream fixes merged and credited
testing methods in Cernos
129
testing methods in Cernos
Now
Four fixes merged into ffn and credited in its v1.3.0 release notes, one into skfolio v1.4.1; quantstats and Databento fixed what I reported. PRs are open at Goldman Sachs, Microsoft Qlib, barter-rs, and Alpaca.
Next
A 90-day pre-registered paper-trading track, kill conditions committed on day 0.

Why hire me: decisions, and how I checked them

  1. How do you set an exit when the training data holds two trades?

    Thought
    Two engine cycles per variant is too few to fit anything. A fitted exit would only be a search that looks like a result.
    Tested
    Derived it from costs instead: take-profit at 450 ticks, which is 346 of round-trip maker fees plus 55 of measured one-second drift plus a margin, and an exit at the touch after 60 seconds.
    Result
    No free parameter was left to overfit, so the test that followed judged the idea, not the tuning.
    Proof
    Liquidity Engine study

  2. Was the gate's edge real, or one lucky session?

    Thought
    Session D's advantage (t ≈ 2.3 on six cycles) came from the only session I had already looked at.
    Tested
    Committed three hypotheses, the variants, the commands and the exits before replaying session E, against an ungated control with identical exits.
    Result
    All three hypotheses failed. I reported it as registered, and the README leads with the negative result.
    Proof
    Evidence page

  3. Is a copied trading rule the vendor's rule, and does it survive costs?

    Thought
    A rule can match a vendor's trades and still be noise once spread and commission are paid.
    Tested
    Inferred a fade rule that matches 88% of one vendor's 2026 trades, tuned filters on January to June and judged them on July to October, then audited costs on live demo fills: $7.33 per lot round trip against the $7 assumed.
    Result
    Only 33% of profitable setups held up, and one-shot holdouts failed after costs. Nothing went further than a demo forward test.
    Proof
    Private research repo, described

  4. Are the numbers in the quant libraries everyone uses correct?

    Thought
    Performance statistics are easy to get subtly wrong and rarely checked against reference values.
    Tested
    Ran reference-value tests and benchmarks against ffn, skfolio, quantstats, Databento dbn, gs-quant, Qlib and barter-rs, and retested every bug on a fresh clone before filing.
    Result
    Five fixes merged and credited (ffn v1.3.0, skfolio v1.4.1); quantstats and Databento fixed what I reported.
    Proof
    github.com/Astralchemist

Experience

  1. Dec 2025 to Present
    Dubai, UAE · remote

    The Change Intelligence Platform · Lead engineer (contract), then maintainer

    • Built and shipped the platform solo in six months, Dec 2025 to Jun 2026, from architecture to production, under the direction of change-management practitioners. On retainer since for maintenance and feature work.
    • Multi-tenant change-management SaaS: Next.js and FastAPI on a Docker Compose stack with Supabase. Fine-tuned Llama 3.1 8B and served it with vLLM on a Modal L4 GPU, behind an OpenAI-compatible API with an OpenRouter fallback.
    • Four role-based tiers, including a delegated Champion portal with magic-link auth, PDF export via Puppeteer, a seven-tag sentiment model, and an automated LinkedIn outreach pipeline.
    • Led a latency and build-performance pass after an audit surfaced I/O-wait bottlenecks and N+1 query patterns.
    • Next.js
    • FastAPI
    • Python
    • Supabase
    • PostgreSQL
    • Docker Compose
    • Llama 3.1 8B
    • vLLM
    • Modal
    • OpenRouter
    • Puppeteer
  2. Oct 2025 to Present
    Dubai, UAE · remote

    Early-stage stealth startup · Technical advisor, algorithmic systems

    • Joined as lead algorithmic engineer at the founding stage, then moved to an advisory role while funding closes.
    • Designed the backtest-as-a-service API: FastAPI, TimescaleDB, a Redis cache keyed on the strategy hash, and per-key rate limits.
    • Python
    • FastAPI
    • TimescaleDB
    • Redis
  3. 2024 to 2025
    Nairobi · hybrid

    ConsultHasha · Principal systems engineer

    • Early engineer at a startup. Designed and built the REST API layer and the production service endpoints the product and its client integrations ran on.
    • Owned architecture, deployment, and reliability.
  4. 2020 to 2025
    Remote

    Upwork · Freelance quant and full-stack developer

    • MQL5 and MT5 Expert Advisors built to client risk specifications, then Python backtesting tools, Telegram signal bots, and execution dashboards.
    • Also Docker-first Next.js and Postgres client platforms.
    • MQL5
    • MetaTrader 5
    • Python
    • Telegram bots
    • Next.js
    • PostgreSQL
    • Docker

Education

  • Sep 2022

    Mount Kenya University · Computer Science

Projects

  1. Cernos

    Strategy research engine in Rust, LEAN indicators ported

    Pre-release · private repo

    A terminal tool that finds trading strategies on the web, translates them into one JSON format with an LLM, checks each translation against the original code in a sandbox, backtests and breeds them, and exports the winner as standalone Python or C++.

    241 indicator types ported from LEAN · 129 testing methods · 8 source languages translated

    Hard: Counting every parameter trial. The first gauntlet records each parameter set it tries and judges with CSCV/PBO and a probabilistic Sharpe of at least 0.95, so tuning cannot hide in the result. The first BTC-USD run failed all 12 trials.

    Private repo, architecture only

    Rust · OpenRouter LLM loop · Sandboxed containers · Python and C++ export

  2. Strategy Rebuilds

    16 published FX and gold systems, reverse-engineered

    In progress · private

    Rebuilt published MyFxBook systems from their trade logs: profiled 16, inferred their entry rules, and ported the strongest to MT5 and to a core-plus-adapters Python kit where session, trend and pause filters attach without touching the entry logic, then tested them on real broker ticks.

    16 systems profiled · 88% of one vendor's trades matched by the inferred rule · 218 trades reproduced exactly

    Hard: Separating an edge from tuning. Filters were chosen on January to June 2026 and checked on July to October; only 33% of profitable setups held, and one-shot holdouts with hashed configs failed after costs. Live demo fills then confirmed the cost model.

    Private repo, architecture only

    MQL5 · MT5 real-tick tester · Python · Dukascopy and broker ticks

  3. Liquidity Engine

    BTC order-book research, pre-registered

    Public · negative result

    A deterministic Rust engine that records BTC perpetual order books on three venues, replays them exactly, and tested a market-making strategy that does not work at retail fees.

    47–67% variance from OFI · 41–66 ticks drift at 1 s · 3 venues, exact replay

    Hard: Measuring what a fill costs. Probes resting at the touch saw 41 to 66 ticks of adverse drift within one second on every venue, in every session, under every fill model.

    Evidence page · Study, eleven figures · Source

    Rust · WebSocket feeds · L2 queue model · Python figures

  4. Backtest API

    Trading infrastructure

    Private, described architecturally

    Backtest as a service: the boring parts, built so the same strategy is never computed twice.

    5×3 pairs × timeframes · 60/min rate limit · hash cache key

    Hard: Cache keys that survive strategy edits. The same strategy is asked for a hundred ways, so the key is the strategy hash, not the request.

    Private repo, architecture only

    Python · FastAPI · TimescaleDB · Redis · Docker

  5. Signly

    Forex signal verification

    Maintained, not live

    Verify Telegram trading signal channels before trusting them. Built and shipped, and maintained; not live, with the public site offline.

    5 iterations · 11 mo to product · 5 what-if exits

    Hard: Parsing free-text signals reliably, and defining a verdict that penalises stop-loss indiscipline instead of rewarding win rate.

    Maintained, not live

    Python · FastAPI · Polygon · PostgreSQL

  6. Trading Strategy Library

    Public quant work

    Open source

    A strategy catalogue plus research tools, from indicator to execution to statistics.

    4 strategy families · 5% max risk per trade · 1:1 breakeven move

    Hard: Keeping research honest. The research suite is labelled research-only in its own README, and that label stays.

    Quant-Algos · Expert-Advisor v0.5.1 · MT5 Expert Advisor

    Python · MQL5 · NumPy · QuantConnect Lean

  7. Rig

    Semantic codebase graph over MCP

    npm v0.3.0 · Show HN

    npx rig-constellation gives a coding agent a map of the codebase instead of grep. Local-first, no key, nothing uploaded.

    ~100 commits, 4 days · 6 index stages · 3 agents wired

    Hard: About 100 commits in four days to v0.1.5, stable per-project ports, and keeping the map live during indexing.

    npm: rig-constellation · Source

    TypeScript · MCP · Node · SQLite

  8. CreditWatch

    Cloud-credit runway from the menu bar

    1.0.0 released 2026-09-21

    Answers one question: how long does the prepaid GPU credit last at the current burn.

    10% runway buffer · 72 h history kept · 1.0.0 not 0.1.0

    Hard: The account schema documented balance. A live account proved the spendable figure is credit. Windows and Linux were built and unit tested but not claimed, because no human had run the installed binary.

    GitHub release 1.0.0 · CHANGELOG and ROADMAP

    Kotlin · Compose Desktop · SQLite · Keychain

  9. StickyInc

    Commitment pane fed by MCP

    v0.5.1 · v0.6 in review

    Tell an LLM to call the dentist Friday, an MCP tool call fires, and a checkbox appears on screen. No backend, ever.

    0 backends · 4 agent CLIs detected · every tag released

    Hard: Detecting whichever agent CLI is installed without asking for a key or a config file.

    Releases

    TypeScript · Rust · Tauri · MCP

Also: Zoetrope (Rust, deterministic HTML-to-video, pre-alpha); Trading-System-CI (QuantConnect Lean in Docker with an Optuna rebate optimizer); Meridian, Ledgerly (client and SaaS platforms, Docker-first Next.js and Postgres).

Upstream fixes to quant and trading libraries

Bugs found by reference-value tests and benchmarks, reproduced with failing tests, and reported with a fix.

  • ffnThe ulcer performance index was not annualised, rounding residue counted as tracking error, short lookbacks missed month-end anchors, and 3y, 5y and 10y returns were reported without enough history. Four PRs merged, credited by name in the v1.3.0 release notes.
  • skfolioDrawdown measures ignored a loss on the first observation, so they disagreed with the optimizer. PR merged the same day, listed in the v1.4.1 release notes.
  • quantstatsThe probabilistic Sharpe ratio used the wrong kurtosis and could return a probability above 1. All three bugs confirmed by the maintainer, fixed in v0.0.82.
  • Databento dbnThe symbol map stored one entry per day per mapping, 1.73 GB at 20,000 instruments, and the test suite failed without a feature flag. Both fixed by the maintainers, released in 0.71.0 and 0.72.0.
  • gs-quantGoldman Sachs' toolkit: a correlation crash, Sortino computed over losing days only, Sharpe on two clocks, an RSI seed, and backtest P&L that counts the starting capital. Six issues and five fix PRs open; the first was reproduced independently by another contributor.
  • QlibMicrosoft's risk_analysis max drawdown ignored a loss in the first period, the same bug as skfolio's. PR open.
  • barter-rsThe tear sheet showed the loss rate as the win rate, and got profit factor and Sortino wrong. PR open.
  • Alpaca MCPGenerated trading tools carried no read-only or destructive hints, so a client could not tell a quote from an order. PR open.

Findings from live verification

  • Scope the promise, not the codeCreditWatch 1.0.0 was built and unit tested on Windows and Linux. It claims macOS only, because no human had run the installed binary on the other two. The code shipped. The claim waited.
  • Trust the live system over the schemaThe provider's account schema documented a balance field. A live account proved the spendable figure is credit. The monitor now reads credit, and the finding is quoted in the CHANGELOG rather than hidden in a commit.
  • Alerts must not fire on the pastA 6-hour alert armed when runway is already 4 hours fires immediately and teaches the user to ignore it. CreditWatch refuses to arm any threshold below the current runway, and says so in the dialog.

Numbers as of 2026-11-03. No live P&L is claimed.