INITIATING COVERAGE · JUN 2026 · FRANKFURT
Siddharth Jain
Full-stack AI engineer: agentic systems for finance. MSc AI & Data Science, Frankfurt School. CFA Level 1 candidate.
Siddharth ships agentic AI systems that hold up under audit: every number deterministic, every claim cited to source, every model evaluated against a labeled oracle before it speaks. Nine systems run live today across regulation, credit, AML surveillance, and investment research, on real EUR-Lex, SEC EDGAR, and market data. He is in Frankfurt, looking for the fintech, bank-AI, or quant team that takes evidence as seriously as he does.
- Production systems (Suzlon, CEO office)
- 7 GenAI bots · 14 BI dashboards · 300+ daily users
- shipped 2025–26, 10 plants
- Location
- Frankfurt am Main · from Aug 2026
- Availability
- Internships & Werkstudent · from Sept 2026 · up to 20 h/week in lecture periods, full-time in breaks
- Work eligibility
- Eligible to work in Germany under student regulations
- Education
- MSc AI & Data Science, Frankfurt School (2026–) · CFA Level 1 candidate
- Languages
- English (fluent) · German (active learner, B1 target 2026) · Hindi (native)
Coverage
19 systems under coverage, grouped by desk. Every metric is measured, not estimated — evidence and methodology live in each case note.
Flagships
19 systemsstatus live from Hugging Face
More on github.com/sidnov6
Track Record
THE JOURNEY · DELHI → FRANKFURT
2026 –
FRANKFURT
2026 – · FRANKFURT
MSc Artificial Intelligence & Data Science1
Frankfurt School of Finance & Management · FRANKFURT, DE · IN PROGRESS
- Specialising in applied AI for financial and industrial systems.
- Research focus: enterprise LLMs, agentic finance, and data-intensive AI systems.
2025 – 26
PUNE
2025 – 26 · PUNE
AI Engineer — CEO Office, Manufacturing
Suzlon Energy · PUNE, IN · FULL-TIME
- Drove the BI and GenAI rollout across Suzlon’s manufacturing plants in Asia and Europe — dashboards and RAG + SQL agents in daily enterprise use across Quality, Safety, Production, Energy, and HR.
- Built the Manufacturing Control Tower in a 6-person engineering team — a consolidated executive view of plant KPIs across safety, quality, productivity, delivery, cost, manpower, and environment.
- Helped rebuild the monthly Manufacturing Business Review — data sourced and modelled from 50+ operational systems, with agentic AI answering live questions with on-the-fly charts.
2024
ATLANTA
2024 · ATLANTA
Cybersecurity Summer Intern
Georgia Tech · ATLANTA, US · RESEARCH COMPUTING & DATA
- Selected as 1 of 10 students from India, from 10,000+ applicants.
- Built patient-data pipeline security middleware bridging legacy hospital systems with modern cloud EHR platforms.
- Solved 50+ critical integration failures across US healthcare systems, enabling production-ready data exchange.
2024
ATLANTA
2024 · ATLANTA
AI Research Intern — Medical Imaging
Coulter BME (Georgia Tech × Emory) · ATLANTA, US · SARCOPENIA PIPELINE
- Built an automated sarcopenia-assessment pipeline from CT scans under Dr. Rakesh Shiradkar — from data prep to production inference.
- 94% prediction accuracy on 1000+ CT scans with <1 s inference per scan — down from ~10 minutes of manual analysis.
2023
JAMMU
2023 · JAMMU
Research Intern — 5G & Network Security
IIT Jammu · JAMMU, IN
- Designed a containerized IDS/IPS deployment for secure traffic routing in 5G networks, under Dr. Samaresh Bera.
- 19% throughput improvement under peak-load conditions.
2021 – 25
VELLORE
2021 – 25 · VELLORE
B.Tech — Information Technology2
VIT Vellore · VELLORE, IN · COMPLETED
- Completed 3 international research internships during undergrad — Georgia Tech, Coulter BME (GT × Emory), IIT Jammu.
NEXT STOP: FINANCE × AI, FRANKFURT
1. Frankfurt School: ranked #32 worldwide in Finance & Management (FT Global Rankings).
2. VIT Vellore: CGPA 8.36/10 · ranked #12 in India (NIRF + QS rankings).
PIPELINE · SOURCE TO PRODUCT
SOURCES
50+ enterprise systems
- SAP ERP
- SQL Server
- Salesforce
- SharePoint
- Workday
TRANSFORM
ETL / ELT · real-time + batch
- Spark
- dbt
- Airflow
LAKEHOUSE
Snowflake · Databricks
- Bronze — raw
- Silver — cleaned
- Gold — business-ready
AI / BI
Dashboards · GenAI · ML
- BI dashboards — Power BI · Tableau
- GenAI chatbots — LangChain · RAG
- ML models — PyTorch · Scikit-learn
- Predictions — forecasting · anomaly
One owned path — from enterprise source systems to the AI and BI products in daily use.
SKILLS MATRIX
Role
What I ship
Data Engineer
Production pipelines and Bronze → Silver → Gold lakehouse layers — real-time ingestion and batch.
Data Scientist
Forecast and risk models in production — deep learning across tabular, vision, and NLP, with rigorous A/B tests and causal analysis.
Data Analyst
Executive dashboards driving daily operations, stakeholder-facing storytelling, and self-serve BI for non-technical teams.
GenAI Engineer
RAG systems and multi-agent workflows in production, with eval frameworks for LLM quality and drift.
Foundation: Python · SQL · AWS · Azure · Docker · Git / CI-CD · Linux
OUTLOOK
The pivot to finance
One year of manufacturing AI at the CEO Office showed me what AI can do at scale. Now — back at Frankfurt School full-time — I am taking that playbook to finance. To build the right AI agents for finance, you need to speak the language of money, so alongside the MSc I am pursuing the CFA Level 1.
CFA L1 · 2026 sitting · study progress 35%
If you build, hire, or mentor in finance × AI: reach out.
Profile
Off the screen: national-level basketball — a point guard who learned to read situations in real time, lead under pressure, and trust teammates. And a die-hard Manchester United supporter through every trophy and every rebuild — belief in systems even when short-term results disagree.
I follow geopolitics the way some people follow football — analytically, with strong opinions: Indo-Pacific power shifts, EU economic architecture, energy markets. Competitive debate — collegiate competitions and Model UN — made me a sharper thinker and a better presenter to CXO stakeholders.
The other constant is teaching: Python and mathematics across 4 government schools in Tamil Nadu, plus weekly AI-literacy sessions in Pune — 250+ students taught in total.
As Operations & Marketing Head of the ACM student chapter at VIT, I raised $11K in sponsorships through 200+ cold calls and ran multi-day events with 500+ participants.
Delhi → Vellore → Atlanta → Pune → Frankfurt
Notes
Research notes on agentic AI, evaluation, and finance.
- RED QUEEN: Training an AML Detector Against Crimes That Do Not Exist Yet
Conventional transaction surveillance can only catch the patterns someone already wrote a rule for. It is structurally blind to the typology nobody has seen. RED QUEEN manufactures those unknown-unknowns on purpose, in a closed synthetic loop, and hardens a detector against them before they appear in the wild.
- DELPHI: Build the Skeptic Into the Architecture, Not the Prompt
LLMs fail at finance in one specific way: a confident model recalls a plausible but wrong figure, and a single-pass pipeline has nothing to catch it. Sell-side research solved this structurally decades ago — specialists draft, a skeptic challenges, compliance gates publication. DELPHI makes that workflow the architecture.
- CADUCEUS: Pressure-Testing Agentic AI on the Highest-Stakes Domain There Is
A molecular tumor board is the textbook case for multi-agent AI — and the textbook case for getting AI in medicine wrong. CADUCEUS convenes 55+ specialist agents across 7 layers, argues against its own consensus, and lets nothing reach a human without a retrievable source. The patterns are the finance patterns, on the hardest possible stakes.
Request coverage
Roles, collaborations, or a methodology question: direct line below.
Direct line
Frankfurt, Germany
Job specs welcome. So are geopolitics debates.