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Independent Consultant in Agentic AI, Scientific Computing, and Quantitative Systems Architecture
Contact: augusto [dot] kiel [at] gmail [dot] com
Executive Profile
Scientific software engineer and independent consultant with a physics background and experience in quantitative finance and scientific R&D (J.P. Morgan, Qontigo, SimCorp, Mercado Libre, AstraZeneca). I help teams investigate numerical performance, build reproducible research software, and evaluate AI workflows. My experience includes pricing and risk libraries, scientific computing, and enterprise AI integration and evaluation, spanning Research Software Engineering (RSE), High-Performance Computing, and Production-Grade AI Engineering.
My Physics degree (Licenciatura, University of Buenos Aires) taught me to find the right level of abstraction before writing a line of code. Seven years across J.P. Morgan, Qontigo, SimCorp, and Mercado Libre taught me what production actually costs.
Core expertise: High-Performance Computing • Neural Stochastic Differential Equations • Agentic AI platforms • Multi-asset pricing systems • Risk analytics • DSL development • Numerical optimization • Python/C#/Julia • System Architecture
Engagement Focus: Performance Optimization Sprints, Agentic Platform Integration, Knowledge Engine Architecture, Agent Evaluation Frameworks, RSE Consulting, DSL Design, Architectural Design Sprints, Specialized Corporate Training.
Consulting Services
Agentic AI Engineering
- Production-grade Model Context Protocol (MCP) server design and implementation
- Multi-tenant enterprise authentication architecture (OAuth 2.0 PKCE, Grant Chains, CCG)
- Competitive Intelligence Knowledge Engines: document ingestion pipelines, hybrid RAG, IR trace optimization
- Automated Agent Evaluation (Evals) frameworks for task accuracy, tool-calling reliability, and retrieval stability
- Multi-layer agent memory systems (episodic, semantic, working memory) and personalization engines
- LLM security architecture and threat modeling for advanced reasoning models
- Agentic cost engineering: pre-filtering, caching, and execution graph optimization
Research Software Engineering (RSE)
- Translating research-quality code into stable, reproducible production systems
- Neural Stochastic Differential Equations (NeuralSDEs) and physics-informed ML for scientific simulation and quantitative finance
- Standardizing analytical workflows from Jupyter notebooks to CI/CD-managed pipelines
- Reproducibility, testing, and DevOps practices for R&D and Quantitative Finance teams
- Scientific computing architecture for high-mathematical-complexity domains
- Migration and modernization of legacy analytical systems
High-Performance Computing (HPC) Sprints
- Performance audit and optimization for numerical bottlenecks
- Vectorization, caching, and parallelism strategies
- Improved pricing performance to support real-time risk calculations in production systems
- Real-time computational finance optimization
- Multi-asset class pricing and valuation frameworks
Domain-Specific Language (DSL) Architecture
- Custom language design for complex pricing models
- Interactive UI development for quantitative libraries (ipywidgets, Voilà)
- Simplifying access to sophisticated mathematical models for non-engineer users
Training & Knowledge Transfer
- High-Performance Numerical Computing with Julia workshops
- Research Software Engineering (RSE) best practices for scientific teams
- Corporate workshops on quantitative finance and computational methods
- Technical mentorship for quant and engineering teams
- Interactive educational materials using Jupyter notebooks
Education
Licentiate degree in Physics, University of Buenos Aires (2011-2017)
Signature Case Studies
1. The Performance Optimization Sprint (Qontigo)
The Challenge: Critical risk calculations were too slow for real-time reporting due to unoptimized convertible bond pricing engines.
The Solution: Led a forensic performance audit and implemented cache optimization strategies in the core C# numerical library.
Outcome: Improved convertible bond pricing performance to support real-time production risk reporting and reduced Azure compute spend.
2. The Scientific AI Implementation (Research/SimCorp)
The Challenge: Traditional Monte Carlo simulations for European Option Pricing were computationally expensive; standard AI lacked mathematical constraints.
The Solution: Managed research into Neural Stochastic Differential Equations (NeuralSDEs) using Julia, combining deep learning with physical laws. Parallelly developed an LLM-based RAG system for querying complex financial documentation.
Outcome: Researched and evaluated NeuralSDE solutions against traditional solvers and established a framework for “Safe AI” in financial contexts.
3. The “Quant Experience” Architecture (SimCorp)
The Challenge: Quants struggled to interact with complex underlying pricing models, leading to errors and slow iteration.
The Solution: Designed and developed a Proof-of-Concept Domain-Specific Language (DSL) and integrated interactive Jupyter-based UIs (Voila/ipywidgets).
Outcome: Enabled non-engineers to safely construct and test pricing logic by abstracting underlying complexity.
4. The Enterprise Agentic Platform (AstraZeneca, Oncology R&D)
The Challenge: An R&D agentic platform needed a complete external-integration surface, a measurable quality framework, and reliable knowledge retrieval — none of which existed.
The Solution: Architected production-grade MCP servers with multi-tenant OAuth patterns; built automated Evals frameworks to quantifiably measure agent task accuracy and tool-calling reliability; designed document ingestion pipelines and optimized IR traces for a Competitive Intelligence Knowledge Engine; engineered multi-layer agent memory and personalization systems.
Outcome: Delivered the full external integration layer to production; established reusable OAuth blueprints adopted for all subsequent integrations; implemented semantic pre-filtering and caching to reduce LLM token consumption; established an Evals suite tracking tool-calling accuracy and retrieval precision as ongoing KPIs.
Professional Experience
AstraZeneca
Senior AI Engineer (Independent Contractor) March 2026 - August 2026 | Remote
Advancing the R&D Agentic Platform and strengthening internal developer enablement for agent-based workflows.
- Enterprise Agentic Integrations: Architected and shipped the external integration surface of the R&D agentic platform, designing production-grade Model Context Protocol (MCP) servers with robust multi-tenant authentication patterns (OAuth 2.0 PKCE, Grant Chains, and Client Credentials).
- Competitive Intelligence & Knowledge Engines: Built automated document ingestion pipelines to index enterprise sources into the LLM-Wiki/Knowledge Base. Tuned hybrid search (dense + sparse) and analyzed IR traces to cut retrieval latency and improve source hit rate.
- Automated Agent Evaluations (Evals): Designed and ran automated evaluation frameworks measuring agent task-execution accuracy, tool-calling reliability, and retrieval stability across model updates.
- Multi-Layer Memory & Personalization: Built user content personalization engines and structured agent memory systems—episodic, semantic, and working memory layers—so agents return context-relevant responses rather than generic ones.
- LLM Security & Threat Modeling: Audited tool-use capabilities in advanced reasoning architectures, identifying and neutralizing critical tool-injection vectors and token-abuse vulnerabilities before execution in production.
- Agentic Cost Engineering: Optimized execution graphs through semantic pre-filtering and custom cache optimization layers to reduce LLM token consumption.
Phorma
Co-founder & Research Software Engineer February 2026 - Present | Buenos Aires, Argentina
Co-founded Phorma with Agustín Corbat to apply Research Software Engineering (RSE) to R&D and Quantitative Finance teams. Scientists keep their research focus; Phorma owns the engineering execution.
- Transforming research-quality models and workflows into stable, reproducible production systems
- Designing RSE architectures for scientific simulation and quantitative finance
- Establishing engineering best practices (testing, CI/CD, reproducibility) in high-mathematical-complexity codebases
Independent Consultant
Quantitative Software & Scientific Computing January 2026 - Present | Buenos Aires, Argentina
Providing specialized consulting services to financial institutions and technology companies:
- Quantitative finance system architecture and development
- Scientific computing and numerical software optimization
- Technical leadership and team mentorship
- Developer experience and tooling for analytical platforms
Focus areas: Multi-asset pricing libraries, risk analytics systems, DSL development, performance optimization, Python/C#/Julia consulting.
Mercado Libre
Software Technical Lead, IT Staff / Financial Planning & Analytics June 2025 - March 2026
Leading technology strategy and managing 14 engineers across Financial Planning & Analytics for Latin America’s largest e-commerce ecosystem.
Key Focus: Strategy, Standardization & AI Workflows
- Architecting scalable financial planning and analytics platforms
- Championing AI-assisted development workflows and clean architecture standards
- Transforming ad-hoc Jupyter analyses into CI/CD-managed production systems
Impact: 90% reduction in forecasting pipeline errors through RSE principles; 15% velocity increase across engineering team
Technologies: Go, TypeScript, Python, BigQuery, Jupyter, CI/CD, distributed systems
SimCorp
Lead Software Engineer, Core Analytics March 2024 - May 2025 | 1 year 3 months
Key Focus: Core Analytics & Quant UI
- Developed Domain-Specific Language (DSL) POC for pricing model interaction
- Created LLM-based RAG system for financial documentation Q&A
- Integrated Quant UI with Axioma Risk UI for institutional investors
- Redesigned libraries for Automatic Differentiation (AD) support
Qontigo (Axioma Risk)
Associate Principal, Core Analytics September 2020 - March 2024 | 3 years 7 months
Key Focus: Core Quant Libraries & High-Performance Computing
- Designed and developed core Quant Monorepo (C#) for Analytical Libraries
- Managed NeuralSDE research internship for European Option Pricing using Julia
- Built Axioma Pricing Library (APL) from the ground up, with comprehensive validation tests
- Developed comprehensive curve construction library (rates, yields, discounts, spreads)
- Led development of interactive UI (ipywidgets/voila) for Quant library access
Impact: Improved Convertible Bond Pricing Engine performance to enable real-time production calculations; “Exceptional Performance” rating (2023)
J.P. Morgan
Technology Analyst, Rates CIB July 2018 - August 2020 | 2 years 2 months
- Built production-grade financial reporting systems with zero-downtime requirements for Rates CIB
- Provided critical support to Rates Quant team, enhancing analytical capabilities
- Delivered infrastructure for mission-critical reporting services ensuring compliance and reliability
Open Source Contributor & Content Creator
Scientific Software & Educational Tools February 2016 - Present | 9+ years
@sashakile | @akielbowicz | YouTube: @SCA314 | GitHub: SCA314
- Creator of SCA314, an educational YouTube channel focused on software craftsmanship, scientific computing with Julia, and automated testing practices in Spanish
- Development of interactive educational materials based on Jupyter notebooks
- Contributions to scientific computing and data visualization projects
- Created charly-vibes (site, GitHub) as a personal R&D lab for agentic coding experimentation, exploring the limits of Structured Vibecoding
- Educational content bridging academic knowledge and industry best practices
Teaching Experience
University of Buenos Aires
- Professor of Calculus and Linear Algebra, CBC Engineering (December 2020 - July 2022)
- Teaching Assistant on Summer Course of Optics and Thermodynamics for Biology and Geology (February 2015 - March 2015)
- Science Communicator at Physics Department (March 2013 - December 2014)
Southern International School
- High School teacher of Physics, Mathematics and Information Technologies (2016)
Publications
Shared Memory Semi-Implicit Solver for Hydrodynamical Instability Processes (2023)
Photon Counting Module based on Avalanche Photo-Diodes (2017)
Speaking & Community
Active participant in technology conferences and meetups as speaker and collaborator:
- SciPy Latinoamérica 2022 (Argentina): Workshop presenter
- Regular speaker at Python and Julia user groups in Buenos Aires
- Represented Qontigo at ECI UBA (School of Information Sciences, University of Buenos Aires)
All talks available at: talks.saxa.xyz
Technical Skills
Programming Languages Production: Python, C#, Julia Functional/Niche Languages: F#, Clojure
Agentic AI: Model Context Protocol (MCP), LangChain, LangGraph, LlamaIndex, RAG pipelines, vector databases, AWS Bedrock, multi-agent systems, LLM Evals, enterprise OAuth (PKCE, OBO, CCG)
Research Software Engineering: Reproducible workflows, scientific Python stack, numerical methods, automatic differentiation, stochastic differential equations, NeuralSDEs
Quantitative Finance: Multi-asset pricing, risk analytics, derivatives valuation, curve construction, model calibration
Architecture & Leadership: DSL design, API design, monorepo infrastructure, microservices, Technical Mentorship, Solution Design, Corporate Training
Tools: Jupyter, Git, Docker, Azure, GitHub Actions, Visual Studio
Available for consulting engagements globally (remote) and in Buenos Aires
Contact: augusto [dot] kiel [at] gmail [dot] com