Senior AI Engineer (Studio)
Full-time
Hybrid
Flatiron District, Manhattan, New York, NY
$190K - $250K
Role highlights
Intake call
Requirements
Pipeline
About this role
Interview process
Ideal candidates
Rejected feedback
Announcements
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Primary recruiter
Start recruiting
Suhaas Kiran D.G.
1 recommended candidate from your network
Tommy Garry
Tommy Garry
Lead
Highly engaged
Top 10% of hiring managers
Time to first action
26 hours
Reply time
3 days
Active days
10 days
Feedback quality
Clear
Latest announcement
· Sep 18, 2026
We are looking to hire 2-3 candidates into this role. Have only seen 8 candidates this week and we are looking for more (while keeping the bar extremely high please!)
Role highlights
Hiring goal
3 - 4 candidates
Recruiter activity
Recruiter activity on this role is medium
No final round interviews
There currently aren't any candidates in final round interviews or offer stage
Why candidates should join
Real ownership across four pillars. You don't just get base + bonus — you get platform equity (valued as SaaS), studio fund participation in ventures you help build, and carry in an $850M PE fund. Base band is $190K–$225K before all of that.
Founding-engineer energy with enterprise backing. You'll take ventures from validated concept to shipped product with a small team — but backed by real capital and warm distribution from AIVC's consulting arm rather than a prayer and a pitch deck.
Studio ventures = real companies you co-own. AIVC employees get 15% of every business that launches out of the studio. If even one venture hits $100M and you own 1% of that pool — that's an extra $1M+ in your pocket.
High-caliber peer group from day one. The team is ~40 and growing fast. Leadership includes 12-year Citadel AI veterans and BCG alumni. You'll work alongside people who can both build models and talk to customers.
Hybrid in Flatiron (21st & Broadway) or Chicago. ~3 days in-office. Benefits include uncapped bonus potential tied to engagement equity and long-term wealth creation vehicles across studio + fund carry.
Suggested outreach
Intake call
Recorded by Parascribe
Company Overview
AIVC operates as a combination of professional services, a studio for product development, a buyout fund, and a software platform.
Team size is around 40-45, with plans to grow due to increased demand and upcoming projects.
Role Requirements
Hiring for Product Strategist with 3-7 years of experience, preferably from MBB or similar with startup deployment experience.
Looking for candidates with business acumen and product management experience, ideally with technical skills like AI knowledge.
Candidate Requirements
Ideal candidates have a blend of consulting and product management experience, with a strong understanding of AI and business strategy.
Open to candidates from prestigious backgrounds, but Big Four is considered only with additional relevant experience.
Compensation and Logistics
Salary range is $185K - $225K, with potential for higher for exceptional candidates. Includes bonuses, equity, and fund carry.
Visa sponsorship is available, preferably for candidates already in the US (e.g., OPT to H1B).
Timeline and Urgency
Immediate need for two to three builders and one to two strategists for the studio, with a total of about 10 hires across roles.
Company is coming out of stealth in less than 30 days, indicating a need to fill roles quickly.
Interview Process
Four stages: initial chat, product case study, business model design interview, and a behavioral interview.
Specific focus on candidates' past projects and ability to handle new challenges.
Pain Points
Difficulty in attracting junior candidates due to complex compensation model.
Need for candidates with both strategic and technical skills to drive product development and business value.
Ideal Candidate Profile
Entrepreneurial mindset with a strong grasp of both business strategy and technical product development.
Preferably someone who has demonstrated leadership and innovation within both large organizations and startups.
Requirements
By tier
By category
Learn about the ideal background for the product strategist
11:15
Calibrate a candidate in Parabot. to see how well they fit the requirements.
Dealbreaker
Work experience
Evidence of 0-to-1 building — side project, internal tool, or startup that shipped to users (e..g. GitHub, live product, or clear ownership story).
Baseline
Seniority
3 - 7 years of experience end-to-end AI systems to production and operated them after launch:real users, real failure modes, and a post-launch story
Work experience
Shipped end-to-end AI systems to production with real users and real failure modes — not demos, notebooks, or research projects.
Background at a top quant firm or FAANG (e..g. Citadel, Two Sigma, DE Shaw, Google, Stripe, Databricks) — can separate own output from the platform around them.
Education
STEM degree (CS, Math, Physics, Engineering) from a strong university
Hard skills
Built agentic AI systems: agents, retrieval, orchestration, tool integrations, and eval/regression harnesses in production.
Miscellaneous
Commercial EQ: comfortable presenting to non-technical stakeholders, customers, and design partners — not just engineers.
Nice-to-have
Work experience
Archetype A: Engineer from AI-native startup (e..g. Ramp, Modal, Runway, Hebbia, Harvey) or founding/early engineer at a company that shipped product to real users.
Archetype B: QD or quant-adjacent engineer wanting to build product — has startup or entrepreneurial experience alongside quant background.
Traits to avoid
Pure researchers who only want to build models on data with no commercial responsibility or product ownership.
Big Tech engineers who only did incremental improvements to existing systems — no entrepreneurial or 0-to-1 signal.
Job hoppers with no clear narrative — multiple short stints (<1 year) without a coherent reason or demonstrated ownership at any stop.
Pipeline
Your candidates
Analytics
Inbox
3candidates
Intro / Fit Chat with David Sukhin, Head of Studio - 45 minutes
4candidates
Technical Deep Dive / Case Study with Engineering Team - 60 minutes
1candidate
Business Sense / Case Study - 45 minutes
0candidates
Behavioral Interview - 30 minutes
0candidates
Offer
0candidates
Hired
0candidates
Recent Activity
Changed status of Candidate #8 from Submitted to Rejected
an hour ago
Changed status of Candidate #7 from Submitted to Rejected
an hour ago
Changed status of Candidate #6 from Submitted to Rejected
2 hours ago
Changed status of Candidate #5 from Submitted to Rejected
2 hours ago
Changed status of Candidate #4 from Submitted to Rejected
3 days ago
yours
Changed status of Candidate #3 from Submitted to Rejected
3 days ago
yours
Changed status of Candidate #2 from Submitted to Rejected
3 days ago
Changed status of Candidate #1 from Submitted to Mid round
3 days ago
About this role
Hear about the deployment strategist role
10:53
We are looking for a Senior AI Engineer with 3–7 years of experience to join AIVC's Studio as a core builder turning validated venture concepts into shipped products with real users. You're a quant-aspiring or big-tech engineer with an entrepreneurial streak — someone who's shipped end-to-end AI systems to production, built things nobody asked you to build, and wants real ownership in the companies you create.
What will you be doing?
Building end-to-end agentic AI systems (agents, retrieval, orchestration, tool integrations) for Studio ventures from 0→1 through product-market fit
Taking a venture's first product from scope to ship — cutting ruthlessly to the smallest thing that proves value, then hardening it for production
Extracting reusable primitives and patterns from each build so the next venture starts further ahead
Working directly with product strategists and design partners to shape what gets built — not just how it gets built
Operating across genuinely different venture contexts as need dictates, thriving in ambiguity rather than waiting for it to resolve
Key Requirements
2–5+ years at a top quant firm (Citadel, Two Sigma, DE Shaw, Jane Street) or elite tech company (Google, Stripe, Ramp, Databricks, Modal) with clear individual output you can separate from the platform around you
Shipped end-to-end AI systems to production with real users and real failure modes — not demos or notebooks
Demonstrated entrepreneurial instinct: a side project, startup, internal 0→1, or innovation within a large org that shows you don't just execute what's scoped for you
STEM degree (CS, Math, Physics, Engineering) from a top-tier university
Commercial EQ — comfortable working with non-technical stakeholders, customers, and design partners alongside deep technical ability
Role details
Salary
$190K - $250K
Hybrid work policy
3 days in-office in Flatiron District (21st & Broadway), NY or Chicago, IL
Full-time position
Location
Flatiron District, Manhattan, New York, NY, Chicago, IL
Tech stack
Python, LLMs, Agentic AI Frameworks, RAG / Retrieval Systems, ML Model Serving, Evaluation & Regression Suites, CI/CD, Observability / Monitoring
Equity
Competitive equity
Visa sponsorship details
Open to visa transfers (e.g. OPT, H1B transfers)
Hiring Count
Looking to hire 3 - 4 candidates for this role
Report to
https://www.linkedin.com/in/david-sukhin-31559666/
Requirements
By tier
By category
Learn about the ideal background for the product strategist
11:15
Calibrate a candidate in Parabot. to see how well they fit the requirements.
Dealbreaker
Work experience
Evidence of 0-to-1 building — side project, internal tool, or startup that shipped to users (e..g. GitHub, live product, or clear ownership story).
Baseline
Seniority
3 - 7 years of experience end-to-end AI systems to production and operated them after launch:real users, real failure modes, and a post-launch story
Work experience
Shipped end-to-end AI systems to production with real users and real failure modes — not demos, notebooks, or research projects.
Background at a top quant firm or FAANG (e..g. Citadel, Two Sigma, DE Shaw, Google, Stripe, Databricks) — can separate own output from the platform around them.
Education
STEM degree (CS, Math, Physics, Engineering) from a strong university
Hard skills
Built agentic AI systems: agents, retrieval, orchestration, tool integrations, and eval/regression harnesses in production.
Miscellaneous
Commercial EQ: comfortable presenting to non-technical stakeholders, customers, and design partners — not just engineers.
Nice-to-have
Work experience
Archetype A: Engineer from AI-native startup (e..g. Ramp, Modal, Runway, Hebbia, Harvey) or founding/early engineer at a company that shipped product to real users.
Archetype B: QD or quant-adjacent engineer wanting to build product — has startup or entrepreneurial experience alongside quant background.
Traits to avoid
Pure researchers who only want to build models on data with no commercial responsibility or product ownership.
Big Tech engineers who only did incremental improvements to existing systems — no entrepreneurial or 0-to-1 signal.
Job hoppers with no clear narrative — multiple short stints (<1 year) without a coherent reason or demonstrated ownership at any stop.
