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Dedicated AI Engineering Teams

Senior AI Engineers, Dedicated Exclusively to Your Project

Get pre-vetted, full-time AI engineers embedded directly in your organization — working in your Slack, attending your standups, and operating as a true extension of your team. Active within 2 weeks of contract signing.

Traditional Hiring

4–6 months to hire a senior AI engineer
Compete with FAANG for top talent
Full benefits, equity, and overhead costs
Ramp-up takes 3–6 months

Aeologic Dedicated Teams

Active on your project within 2 weeks
Pre-vetted senior engineers, Day 1 ready
No benefits, equity, or overhead costs
Productive from Week 1, not Month 6
2 wks
Average time from contract to first sprint
50+
Enterprise teams deployed globally
90%
Clients extend past 6 months

Available Engineers

SR
Senior LLM Engineer
LangChain · RAG · Claude API · LlamaIndex
Available
ML
ML Engineer
Fine-tuning · PyTorch · Evaluation · vLLM
Available
OPS
MLOps Engineer
AWS/Azure/GCP · Docker · CI/CD · Kubernetes
Available
DE
Data Engineer
Vector DBs · Pipelines · Spark · Airflow
Available
PM
AI Product Manager
Roadmap · Stakeholders · Delivery · OKRs
Available

Onboarding Timeline

Day 1
Contracts Signed
NDA, IP assignment, and DPA in place
Day 2–3
Team Selection
Profiles shared, you approve each engineer
Day 4–7
Tool Access & Onboarding
Slack, Jira, GitHub, codebase access granted
Day 8–14
Sprint Kickoff
First standup, backlog groomed, coding begins
Team Roles

Every AI Engineering Role You Need,
On Demand

We provide the full-stack of AI engineering talent — from senior LLM engineers who architect your system to MLOps engineers who keep it running in production.

Senior LLM / AI Engineer

The core builder of your AI systems. Designs and implements RAG pipelines, LLM integrations, AI agents, and custom AI applications using the latest frameworks and best practices.

LangChain LlamaIndex Claude API OpenAI API FastAPI Python Pinecone Weaviate
Senior level · 5–10 years experience

ML Engineer

Handles model training, fine-tuning, evaluation, and optimization. Builds the learning pipelines that make your AI smarter over time — including RLHF, DPO, and custom evaluation frameworks.

PyTorch Transformers Fine-Tuning RLHF / DPO vLLM ONNX W&B HuggingFace
Senior level · 4–8 years experience

MLOps Engineer

Ensures your AI systems run reliably in production at scale. Builds deployment pipelines, monitoring systems, cost optimization infrastructure, and incident response playbooks.

AWS / Azure / GCP Docker Kubernetes Terraform MLflow CI/CD Prometheus Grafana
Senior level · 4–8 years experience

Data Engineer

Builds the data infrastructure that feeds your AI systems — ingestion pipelines, vector database setup, embedding generation, data cleaning, and real-time streaming from your operational systems.

Apache Spark Airflow Vector DBs Kafka dbt Snowflake ETL / ELT PostgreSQL
Mid–Senior level · 3–7 years experience

AI Security Engineer

Hardens your AI systems against prompt injection, data leakage, model theft, and compliance risks. Implements security architecture, audit trails, and compliance controls for regulated industries.

Prompt Injection Defense SOC 2 GDPR / HIPAA RBAC Encryption Audit Trails
Senior level · 5–9 years experience

AI Product Manager

Bridges the gap between your business goals and your engineering team. Owns the AI product roadmap, manages stakeholder communication, defines KPIs, and ensures every sprint ships to business outcomes.

Roadmap Planning Jira / Linear OKRs User Research Sprint Management Stakeholder Comms
Senior level · 4–8 years experience
Team Packages

Right-Sized Teams for
Every Stage of AI Development

From a single expert engineer to a full AI squad — choose the team configuration that matches your current needs and budget, and scale at quarterly checkpoints.

1

Solo AI Expert

Ideal for: Focused features, POC builds, integration projects

  • • 1× Senior LLM / AI Engineer
  • • Dedicated engagement manager included
  • • Weekly delivery report
₹3–5L / month
~$3,600–$6,000 USD · 3-month minimum
Get Started →
3
Most Popular

Core AI Team

Ideal for: Full AI system builds, production deployments

  • • 1× Senior LLM Engineer (Team Lead)
  • • 1× ML Engineer
  • • 1× MLOps / Data Engineer
  • • Dedicated engagement manager
₹10–15L / month
~$12,000–$18,000 USD · 3-month minimum
Get Started →
5+

Full AI Squad

Ideal for: Enterprise platforms, multi-module programs

  • • 2× Senior LLM Engineers
  • • 1× ML Engineer
  • • 1× MLOps Engineer
  • • 1× Data Engineer
  • • Optional: AI PM + Security Eng.
Custom Pricing
Scoped based on team composition
Talk to Us →
How It Works

Embedded Into Your Team From Day One

Our dedicated teams don't work from a separate silo. They plug directly into your existing workflows, tools, and culture — with zero friction and full accountability.

1

You Select Your Engineers

We share detailed profiles of pre-vetted candidates matching your requirements. You interview and approve each engineer before they join. You always have full choice over who works on your project — no surprises.

2

They Join Your Workspace

Engineers are onboarded to your Slack, GitHub, Jira, Linear, Confluence, and any other tools your team uses. They attend standups, sprint planning sessions, and retrospectives like any in-house team member.

3

Full-Time Exclusive Focus

Your engineers work exclusively on your projects during the engagement. No juggling multiple clients and no split attention. Every engineer is dedicated to your goals, working 40 hours per week as an extension of your team.

4

Weekly Delivery Reviews

A dedicated engagement manager oversees delivery, coordinates HR and administrative support, and conducts weekly review meetings. You gain the productivity of an embedded engineering team without the management burden.

5

Scale Up or Down Each Quarter

Need additional senior engineers for a critical sprint? Need to reduce team size after a major release? Team capacity is reviewed quarterly and adjusted based on your business needs — without penalties, renegotiations, or unnecessary complexity.

Your Team's Daily Collaboration Setup
Your Internal Team
Slack GitHub Jira
↕ Same tools. Same channels. Same standups.
Aeologic Dedicated Engineers
Slack GitHub Jira
Daily standup — your time, your format
Direct Slack DMs — no ticket queue
Sprint reviews every 2 weeks
Code in your repos, docs in your wiki
Weekly delivery report to stakeholders
On-site visits available (India-based teams)

100% IP Ownership

All code committed to your repositories. All models trained on your infrastructure. Full IP assignment signed before Day 1.

From Enquiry to First Code

Your Team Is Active in 14 Days or Less

A step-by-step look at exactly how we take you from initial enquiry to engineers coding on your project in under two weeks.

01
Day 1 — Free Consultation

Discovery Call with a Senior AI Architect

We understand your project requirements, tech stack, team culture, and timeline expectations. You'll receive a proposed team composition and estimated cost within 24 hours.

45 minutes
No commitment
Senior architect direct
02
Day 2–3 — Team Selection

You Review and Approve Engineer Profiles

We send detailed profiles including LinkedIn, GitHub portfolios, technical assessments, and project history for each proposed engineer. You interview anyone you want, reject anyone you don't — final team composition is your decision.

You approve each engineer
No surprises
03
Day 3–5 — Contracts & Legal

NDA, IP Assignment & Data Processing Agreement Signed

Our standard contracts include full IP assignment (100% of code and models are yours from Day 1), a comprehensive NDA, and a Data Processing Agreement (DPA) covering GDPR, HIPAA, and other applicable regulations.

100% IP assignment
GDPR/HIPAA DPA
Full NDA
04
Day 5–10 — Onboarding

Engineers Get Full Access to Your Systems

Tool access is provisioned: Slack/Teams, GitHub/GitLab, Jira/Linear, cloud accounts, and any internal APIs. Engineers review your existing codebase, documentation, and architecture. The engagement manager sets up recurring standups and delivery cadences.

Your tools, your workflows
Codebase review
No surprises
05
Day 10–14 — Sprint Kickoff

First Sprint Starts. Code Ships.

Sprint 1 is kicked off with a groomed backlog, defined acceptance criteria, and a working demo scheduled for 2 weeks out. From this point, your dedicated team delivers working software on a reliable 2-week cadence.

2-week sprint cadence
Working demo every sprint
Code from Day 14
Proven Results

What Dedicated
AI Teams Deliver in Practice

Outcomes from enterprise clients who scaled with our dedicated AI engineering teams.

50+
Dedicated teams deployed globally
90%
Client renewal rate past 6 months
2 wks
Average kickoff time after contract
4.9/5
Average client satisfaction score
"The dedicated team model is fundamentally different from staff augmentation. These engineers know our codebase better than some of our permanent team now. They've been with us 14 months and the thought of losing them is genuinely concerning.
JD
John Davidson
CTO, Fortune 500 Healthcare
"We tried three agencies before Aeologic. The difference is the no-rotation policy. The same two engineers have been on our fraud detection platform for 10 months. The institutional knowledge is irreplaceable. ROI is 400% over our previous agency spend."
SM
Sarah Mitchell
VP Engineering, FinTech Platform
"Hiring AI engineers in Bangalore takes 5–6 months and we still lose them to Big Tech. The dedicated team from Aeologic was productive within the first sprint. We scaled from 1 to 5 engineers in 3 months when our program expanded. Genuinely game-changing."
MR
Michael Rodriguez
Director of Engineering, Industrial Mfg.
Why Choose Us

Dedicated Teams
vs. All Other Hiring Options

How our dedicated model compares across the four common ways enterprises access AI engineering talent.

Factor
Freelancers
Aeologic Dedicated Teams
Staff Aug. Agency
In-House Hire
Time to start
1–2 weeks
✓ 2 weeks, guaranteed
4–6 weeks
4–6 months
Exclusivity
✗ Multiple clients
✓ 100% exclusive
✗ Often split
✓ Full-time
Seniority guarantee
~ Varies widely
✓ Always senior-level
~ Sometimes rotated
✓ You choose
Institutional knowledge retention
✗ Lost on contract end
✓ Builds continuously
✗ Rotation breaks it
✓ Strongest
IP & data security
~ Custom contracts needed
✓ Full IP + SOC 2 + DPA
~ Standard agreements
✓ Full ownership
Scalability
✗ Hard to scale teams
✓ Quarterly flex up/down
~ Possible, with ramp
✗ Slow and expensive
Total cost vs. output
~ Low cost, high variance
✓ Predictable, high output
~ Mid cost, mid output
✗ High cost, slow ramp
AI specialization
~ Hard to verify
✓ Verified AI/LLM experts
✗ Often generalists
~ Depends on hire
FAQ

Frequently Asked
Questions

Everything engineering leaders and HR teams ask before starting a dedicated AI team engagement.

What is a dedicated AI engineering team?

A dedicated AI engineering team is a group of full-time AI engineers assigned exclusively to your organization's projects. Unlike staff augmentation or freelance arrangements, dedicated teams work only for you during the engagement — joining your Slack or Teams workspace, attending your standups, and operating as a seamless extension of your internal team. They build deep institutional knowledge of your systems and deliver consistently without the coordination overhead of agency models.

How quickly can a dedicated AI team start working on our project?

Our dedicated AI engineering teams can be active and coding on your project within 2 weeks of contract signing. The 14-day timeline covers: candidate selection and your approval (Days 2–3), contract and legal paperwork (Days 3–5), tool access provisioning and codebase onboarding (Days 5–10), and sprint kickoff (Days 10–14). For urgent engagements, we can sometimes compress this to 7–10 days. Compare this to 4–6 months for an in-house AI engineering hire going through traditional recruiting.

Can we interview and approve engineers before they join our team?

Yes, always. We will never assign an engineer to your team without your explicit approval. After the initial discovery call, we send detailed profiles including LinkedIn profiles, GitHub portfolios, technical assessment results, and relevant project history for each proposed engineer. You can interview any or all candidates, and you have full veto power over the final team composition. We'll keep presenting alternatives until you're completely happy with the team you're getting.

What is the minimum engagement period?

The minimum engagement period is 3 months. This gives enough time for the team to onboard, build meaningful context about your systems, and ship production-ready work. Most clients extend to 6–12+ months once they experience the productivity and quality of a dedicated team — our renewal rate past the 6-month mark is 90%. Team size is reviewed and can be adjusted (up or down) at quarterly checkpoints with no penalty.

How is this different from staff augmentation agencies?

Staff augmentation agencies typically rotate engineers between multiple clients — meaning your project gets a fraction of someone's attention and institutional context is lost every few months. Our dedicated teams work exclusively on your projects, full-time, for the duration of the engagement. They develop deep knowledge of your codebase, architecture, business logic, and team culture — making them increasingly valuable over time. We also don't rotate our engineers; the same people who start your project stay on it unless you request a change.

Do we own the code and IP the dedicated team produces?

Yes, 100%. Full IP assignment is built into our standard contract — not as an optional clause, but as a non-negotiable default. All code is committed to your repositories. All models, fine-tuning datasets, and prompt architectures are yours. All documentation lives in your wiki. We retain no rights to any work product, and we do not use your systems or data for any purpose beyond your engagement.

What happens if we're not happy with an engineer's performance?

We handle all performance management. If you're not satisfied with any engineer's output, communication, or fit within your team culture, contact your engagement manager and we will begin replacement within 5 business days at no cost to you. We maintain a bench of pre-vetted engineers at all seniority levels for exactly this purpose. Our client satisfaction score is 4.9/5.0 across all engagements — but the guarantee exists because we stand behind every placement.

Are the engineers on-site or remote? Can we meet them in person?

Most engagements are remote, with engineers based in India (Noida/Delhi NCR, Bengaluru, Hyderabad) working in IST timezone — overlapping well with European hours and providing a 9–12 hour window for US-based teams. For clients in India or who want on-site embedding, we can arrange full or part-time on-site presence at your offices. We also support global remote teams across all timezones for the right engagement size.

Get Started

Build Your Dedicated AI Team in 2 Weeks

Tell us what you're building and how many engineers you need. We'll recommend the right team composition, timeline, and pricing within 24 hours.

1

14-Day Start Guarantee

Engineers active on your project within 14 days of contract signing — or your first month's fees are waived.

2

Free Replacement Guarantee

If any engineer doesn't meet your expectations, we replace them within 5 business days at no cost.

3

100% IP Ownership — Always

All code, models, and work product belong to you from Day 1. No exceptions.

Schedule Your Free Consultation

We respond within 4 business hours.

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