AI Developer at UpSolve Solutions LLP · Mumbai · 2 - 4 years · ₹7L - ₹11L / yr · Bootstrapped · Posted 25 Dec 2023

About UpSolve
Work on cutting-edge tech stack. Build innovative solutions. Computer Vision, NLP, Video Analytics and IOT.
Job Role
- Ideate use cases to include recent tech releases.
- Discuss business plans and assist teams in aligning with dynamic KPIs.
- Design solution architecture from input to infrastructure and services used to data store.
Job Requirements
- Working knowledge about Azure Cognitive Services.
- Project Experience in building AI solutions like Chatbots, sentiment analysis, Image Classification, etc.
- Quick Learner and Problem Solver.
Job Qualifications
- Work Experience: 2 years +
- Education: Computer Science/IT Engineer
- Location: Mumbai

About UpSolve Solutions LLP
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Designation: AI Adoption specialist/AI Consultant
Location: Ahmedabad
Work Timings: Primarily Normal Shift (Flexible to support US clients)
Role Overview:
We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.
Key Responsibilities:
Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.
Assess client requirements and prepare solution strategies using AI tools and methodologies.
Work with internal teams to design, propose, and help execute AI-powered solutions.
Provide AI-based recommendations that align with the client’s business objectives.
Communicate technical possibilities in a business-friendly manner to decision-makers.
Take ownership of the client journey from discovery to implementation and support.
Stay updated with AI trends, tools, and real-world use cases that can benefit clients.
Required Skills & Qualifications: Minimum 2+ Years of hands on experience into Custom AI Development. Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency. Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologis). Some hands-on experience in AI projects – either through execution, coordination, or implementation. Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders. Strong problem-solving mind set with the ability to translate business needs into AI opportunities. Flexible to work with international clients, especially in the US time zone as needed.

AI Architect – Enterprise AI & Generative AI ( Remote) - Contractual
Experience: 8+ years
Location: Remote, India
Employment Type: Contractual
Working Hours: 3:00 PM – 12:00 AM IST
Client Engagement: US-based client
About the Role
We are looking for a hands-on, client-facing AI Architect to lead the architecture, technical direction, and production implementation of enterprise AI and Generative AI solutions for a US-based client.
You should combine strong software engineering and cloud architecture fundamentals with practical experience building secure, scalable, and reliable AI applications. This role involves end-to-end technical ownership, from solution design and prototyping to production deployment and optimization. It is not a research-only, advisory-only, or prompt-writing position.
Key Responsibilities
- Lead end-to-end architecture and delivery of AI/ML and Generative AI solutions, from discovery and proof of concept to production rollout.
- Design LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents, and orchestration frameworks.
- Define data ingestion, chunking, retrieval, grounding, evaluation, and knowledge-refresh strategies.
- Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.
- Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.
- Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.
- Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.
- Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.
- Lead technical discussions and design reviews with US client stakeholders.
- Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.
Required Skills & Qualifications
- 8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.
- Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.
- Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.
- Hands-on experience with Python and APIs, including prototyping, code review, and troubleshooting.
- Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
- Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.
- Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.
- Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.
- Excellent written and spoken English, documentation, and stakeholder management skills.
- Availability to work from 3:00 PM to 12:00 AM IST and willingness to accept a contractual engagement.
Preferred Experience
- Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
- Azure AI Search or equivalent retrieval tools.
- LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.
- Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.
- Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.
- Relevant AI/cloud architecture certifications and experience mentoring technical teams.
What Success Looks Like
- Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.
- Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.
- Taking ownership of architecture decisions and resolving technical blockers with limited supervision.
- Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.
Contract Details
- Initial engagement: Minimum 3 months, with extension subject to project requirements and performance.
- Working schedule: 3:00 PM – 12:00 AM IST.
- Potential permanent employment: After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.
Mandatory Screening Criteria
Candidates should be able to:
- Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.
- Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.
- Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.
- Lead a technical design review with US client stakeholders.
- Confirm acceptance of the working hours and contractual engagement.
Apply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.
Build AI where the work actually happens.
Celeco works inside real businesses to understand critical workflows, ship production AI systems and stay through adoption.
We are hiring our first Intelligence Architect (Forward-Deployed AI Engineer).
⌁
Full-time · Remote-first · Optional hybrid in Bengaluru
At least one year of professional engineering experience. Customer travel when the work requires it.
The role
An Intelligence Architect enters a customer environment with an unfinished question and leaves behind a working, measurable system.
This is a hands-on engineering role at the boundary of product, operations and customer delivery. You will learn the domain, inspect the existing systems and data, decide what should be built, and write the code that puts it into production.
What you will own
- Interview and shadow the people doing the work, then map the real workflow, including hand-offs, exceptions and workarounds.
- Understand the customer's application stack, APIs, data, identity model, security constraints and deployment environment.
- Turn business goals into a technical scope, system design, delivery plan and measures of success.
- Build across the stack: AI workflows, data pipelines, integrations, backend services and the interfaces people use.
- Choose the simplest reliable approach. The answer may combine agents, retrieval, rules and conventional software.
- Create evals from representative cases, define quality and failure metrics, inspect traces, red-team the system and set launch thresholds.
- Make practical trade-offs across accuracy, latency, cost, privacy, security and speed.
- Take prototypes into production with tests, monitoring, access controls, documentation and a plan for failure and recovery.
- Work beside customer teams during rollout and improve the system until it becomes part of the workflow.
- Turn what works into reusable components, evaluation sets and playbooks for future Celeco deployments.
You will probably thrive here if
- You have at least one year of professional software or product engineering experience.
- You have shipped a real system used by other people and can explain what you owned, what broke and what you changed.
- You are strong in Python or TypeScript and comfortable moving across unfamiliar codebases, APIs, databases and cloud services.
- You have built with language or multimodal models and understand prompting, structured outputs, retrieval, tool use and model failure modes.
- You use Cursor, Codex, Claude Code or similar tools as part of your engineering workflow, while still reviewing, testing and understanding the code you ship.
- You can create an evaluation set, choose useful quality metrics and improve a system through error analysis instead of prompt guesswork.
- You can speak with an operator, an engineering team and a senior leader without losing the thread of the problem.
- You work well with incomplete requirements, write clearly and surface risks early.
- You care about whether people use what you build and whether it changes a business outcome.
- You can commit full-time and travel to customer sites when discovery or rollout is better done in person.
Experience with cloud deployment, containers, CI/CD, observability, enterprise integrations, authentication or security is useful. We do not expect one person to arrive knowing every framework, cloud or industry.
What you will get
- Direct ownership of live customer problems from discovery through production.
- Close collaboration with Celeco's founders and customer leadership teams.
- Exposure to different industries, operating models and technical environments.
- The freedom to choose the technical approach and the responsibility to prove that it works.
- A role in defining Celeco's engineering methods, reusable systems and technical culture while the company is early.
- A remote-first setup, with the option to work together in Bengaluru.
If the work sounds like you but your background is unconventional, apply. We care more about what you have built, how you think and how quickly you learn than pedigree.
Job Description-
Location- Bengaluru
Experience-5-7 years
Wissen is building the engineering team for RES Modernization, a corporate services programme at a leading global financial services firm, rebuilding the lease and real estate management platform on a cloud stack with AI and agentic capability designed in rather than bolted on. The AI Solution Engineer builds that product: .NET services and APIs at the core, Python wherever the AI, retrieval and data work lives. We want a strong .NET engineer who has moved into Python, not a Python specialist who once touched C#.
- Build features end to end on a .NET codebase: C# and ASP.NET Core services, the APIs above them, and the React or Angular front end where a feature needs one.
- Write the Python that carries the AI work — retrieval and grounding, prompt and agent orchestration, evaluation harnesses, and the pipelines that feed them.
- Put LLM and agentic capability into real product workflows, with the grounding, guardrails and cost and latency budgets a regulated environment demands.
- Take your work through the client's engineering and change review: design notes, test evidence, security and code-quality gates.
- Work with the stream's data and integration engineers on the Snowflake and integration layer the product reads from.
EMBEDDED AI ENGINEERING POD
AI Implementation Engineer Role
Level: AI Implementation Engineer Senior / Advanced - 6+ years
Practice: Wissen GenAI
Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams
Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead
Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.
You deliver production software and help the teams you join work faster.
As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.
Key responsibilities
1. Build and ship.
Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.
2. Embed and enable.
Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.
3. Productionize.
Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.
4. Integrate securely.
Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.
5. Iterate on quality.
Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.
6. Measure.
Track delivery and quality metrics that roll up to the program's targets.
Must-have qualifications
- 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
- Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
- Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
- Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.
Preferred
- RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
- Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
- Prompt engineering as versioned code; building and running evaluations.
- DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
- Financial services or other regulated environments.
- Front-end (React) for AI-assisted UX; streaming and token level operations.
- Azure AI Content Safety and responsible-AI practices.
- Certification: Azure AI Engineer Associate.
What success looks like - first 6 to 12 months
- Multiple GenAI features shipped to production within the embedded delivery pods.
- Measurable adoption and productivity uplift in the teams you support.
- Reusable components adopted from the architects' reference framework.
- Clear contribution to faster time-to-market and lower defect rates.
About the Role
We are a 25-year-old company building toward a technology-centered workforce where AI agents and automation handle more of the day-to-day work, supported by people with specialized expertise.
We are automating our existing workflows, expanding our use of agentic AI, launching a sister company next year, and building a fleet of Hermes AI agents to delegate and manage work.
We are looking for a hands-on AI Systems Architect & Company Technology Lead to help build, connect, and continuously improve these systems.
Key Responsibilities
· Own and improve our Microsoft 365 technology environment and AI-powered workflows.
· Build automations connecting email, meetings, Planner, and other business systems.
· Research, test, implement, and maintain AI tools and integrations.
· Build and manage the Hermes agent fleet, including shared memory, delegation rules, workflows, and reporting.
· Connect AI agents to business systems and SaaS platforms using APIs, webhooks, databases, and automation tools.
· Help build an internal agentic marketing department by selecting and connecting the right AI tools.
· Continuously troubleshoot, improve, and document our technology systems.
· Help apply these systems as the company expands into new ventures.
Must-Haves
· Strong technical problem-solving and self-teaching ability.
· Solid hands-on experience building, configuring, and managing AI agents.
· Experience connecting AI agents and multiple SaaS platforms using APIs, webhooks, databases, and automation tools.
· Comfortable with Python, JavaScript, or similar.
· Ability to independently research, build, test, troubleshoot, and improve systems.
· Strong interest in AI, automation, and emerging technology.
This is a rapidly changing field therefore Direct experience working with actual Hermes agents is not required. However, hands-on experience working with AI agents is required.
What we need is someone who already understands the fundamentals of deploying AI agents, giving them instructions and tools, connecting them to other systems, and making them work reliably in a real business environment.
The Opportunity
This is an opportunity to help us discover and implement what is actually possible with AI today, and to lead the process of expanding workflows along with the rapidly advancing capabilities — this role is not only to implement a technology that has already been figured out.
Position Summary
We are looking for an experienced Enterprise Architect to define and deliver enterprise-scale digital experience architectures leveraging AI/ML capabilities, data platforms, and modern cloud technologies. The role involves partnering with senior business and technology stakeholders to translate business objectives into scalable architectures, strategic roadmaps, and technology solutions.
The ideal candidate will have strong expertise in enterprise architecture, cloud-native technologies, AI-driven customer experiences, and digital marketing platforms, along with the ability to lead architecture initiatives across cross-functional teams.
Key Responsibilities
- Enterprise Strategy & Roadmaps: Define digital, data, and AI strategies, translating business vision into actionable architecture roadmaps aligned with business goals and KPIs.
- Architecture Design: Design end-to-end enterprise and solution architectures integrating digital experience platforms, customer data platforms, AI/ML capabilities, and cloud services.
- Cloud & Technology Architecture: Recommend scalable, secure, and resilient architectures using cloud-native, API-first, microservices, event-driven, and serverless principles across Azure, AWS, or other public cloud platforms.
- AI & Data Architecture: Define architectures for customer data platforms, identity and profile management, data ingestion, governance, personalization, journey orchestration, and AI-powered experiences.
- Architecture Governance: Establish architecture standards, reference architectures, governance frameworks, and operating models to ensure consistency, security, and sustainable technology adoption.
- Stakeholder Management: Collaborate with business leaders, engineering teams, data architects, developers, and data scientists to drive architecture alignment and execution.
- Executive Communication: Lead architecture workshops, visioning sessions, and roadmap presentations, communicating technical recommendations and trade-offs to senior leadership.
- Practice Development: Contribute to reusable architecture assets, mentor architects and consultants, and support presales activities, solutioning, estimations, and proposals.
Required Skills & Experience
- Proven experience in enterprise architecture, solution architecture, and developing enterprise architecture models and roadmaps.
- Strong understanding of architecture frameworks and principles, including TOGAF, SOA, and API-led architecture.
- Hands-on experience with public cloud architecture and services, particularly Microsoft Azure and/or AWS.
- Experience designing and integrating AI-powered solutions, with knowledge of LLMs, prompt engineering, RAG, and model evaluation.
- Understanding of agentic workflows, tool-using agents, and enterprise AI governance, observability, and reliability.
- Experience working with software engineers, application developers, data architects, and data science/ML teams to deliver end-to-end solutions.
- Ability to translate business requirements and strategic vision into technical architectures and implementation roadmaps.
- Strong stakeholder management, leadership, presentation, and communication skills, including experience engaging with senior executives.
- Ability to lead architecture execution across multidisciplinary teams and communicate complex technical concepts to diverse audiences.
Good to Have
- Experience with Adobe Experience Cloud, Adobe Experience Platform, or one or more digital experience solutions.
- Previous experience with other digital marketing and customer experience platforms.
- Experience with customer data platforms, personalization, omnichannel engagement, and marketing optimization initiatives.
- Experience supporting consulting engagements, presales, and enterprise transformation initiatives.
Additional Requirement
- Willingness to travel up to 50%, depending on business and client requirements.
Role Overview
The Principal Architect leads Byteridge’s Technology Strategy & Solutions Group (TSS). This is a senior, visible role responsible for defining technology point-of-view, shaping solution narratives, guiding enterprise conversations, and influencing revenue through differentiated thinking.
The Architect owns thought leadership, reference architectures, solution accelerators, and selective engagement on high-impact deals.
Key Responsibilities
- Own, enhance & execute Byteridge’s technology strategy across priority areas (Cloud, Data, Gen AI, Modernization).
- Create and maintain enterprise-grade reference architectures, solution blueprints, PoCs and accelerators.
- Lead strategic discovery workshops and executive-level solutioning for priority opportunities.
- Partner with Content Marketing to translate technical POVs into blogs, whitepapers, decks, webinars, and sales narratives.
- Enable the Enterprise Account Executive with differentiated solution stories and technical credibility.
- Build strong partnerships with Byteridge delivery teams to identify high-impact solutions and projects that can be leveraged as compelling capability showcases for existing customers and prospective clients.
- Work with Delivery Team Architects to influence delivery standards and architectural consistency across teams.
- Research market and industry trends across technologies, popular enterprise solutions, and buyer adoption patterns. Go deep into selected domains and verticals to continuously refine Byteridge’s technology strategy, solution approaches, and positioning.
- Act as a visible external voice through talks, webinars, and published content.
Ideal Profile
- 13–20 years of experience across technology architecture, solutioning, or technology consulting roles.
- Demonstrated ability to research and synthesize market trends, emerging technologies, and popular enterprise solutions.
- Experience developing deep expertise in specific domains or industry verticals and translating that into solution strategies.
- Strong background in modern software engineering, cloud platforms, data, AI, and enterprise systems.
- Proven track record of influencing client decisions and shaping solution direction, not just designing systems.
- Comfortable working at the intersection of technology, business strategy, marketing, and sales.
- Excellent communication skills with executive presence and the ability to articulate complex ideas clearly.
Success Metrics (KPIs)
- Quarterly technology and market POVs produced and adopted internally or externally.
- Creation and reuse of reference architectures, solution frameworks, and accelerators across deals.
- Number of high-impact delivery projects converted into capability showcases and sales assets.
- Influence on strategic opportunities, measured through deal quality, size, and AE feedback.
- Thought leadership visibility through blogs, webinars, talks, or industry participation.
- Internal adoption of architectural standards and solution approaches by delivery teams.

Overview:
We are looking for a Principal Architect for a Private Equity backed, fast growing AI First Product Engineering Services firm.
This role will be a key member of the core leadership team of the firm.
He/ She will serve as a strategic technical leader, solution designer, and customer advisor. In this role, you will combine deep and broad-based technical expertise with strong business acumen to architect high-value solutions, lead pre-sales engagements, and mentor our practice/CoE team. You will work closely with customers to understand their business needs, translate them into scalable technical solutions, and guide delivery teams in successful implementation.
Responsibilities:
1. Solutioning & Pre-Sales
● Engage with customers, understand their business context, and guide them through a discovery and design process leading to a proposed solution
● Work with sales teams to develop winning proposals, RFP responses, and technical presentations.
● Will need to take single point ownership of the pre sales process, including client interactions, proposal preparation, presentations, pricing etc
● Drive proof-of-concepts as part of the pre sales process
● Build frameworks for different kinds of proposals and presentations to bring in repeatability and efficiency in the process
● Work closely with marketing to create content around Indexnine offerings, solutions, capabilities and case studies
2. Delivery
● Provide technical oversight during project delivery, ensuring adherence to architectural principles, standards, and best practices and ensure the as-sold solution is realised
● Act as a trusted advisor to senior customer stakeholders (CXO level and technical leads). Will need to engage with Customers through delivery as required
● Create points of view on accounts to help mine and grow accounts.
3. Practice & CoE Development
● Work closely with the labs. Contribute to the development of new products/ accelerators.
● Mentor and coach engineers to enhance their technical and customer engagement skills.
4. Thought leadership
● Keep abreast of technology and produce points of view for Indexnine’s offerings and technical capabilities
● Represent the company at industry forums, webinars, and client workshops.
● Be able to independently conduct discovery and solutioning workshops with Customers
Skills/Qualifications:
● 15+ years of overall experience with a blend of architecting, pre sales and technical delivery
● Should be leading a pre-sales unit in a services organization. Hands-on with designing solutions, proposal writing, estimation, pricing and customer presentations.
● Broad based technical expertise and having played a Sr Architect role for at least 2 years
● Excellent communication, stakeholder management, and team leadership skills.
● Experience working in an IT services environment in the Product Engineering space (i.e designing and building bespoke products/solutions)
● BE/ Masters degree
Job Title: AI Architecture Intern
Company: PGAGI Consultancy Pvt. Ltd.
Location: Remote
Employment Type: Internship
Position Overview
We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.
Duration: 6 months
Key Responsibilities:
- AI System Architecture Design: Collaborate with the technical team to design robust, scalable, and high-performance AI system architectures aligned with client requirements.
- Client-Focused Solutions: Analyze and interpret client needs to ensure architectural solutions meet expectations while introducing innovation and efficiency.
- Methodology Development: Assist in the formulation and implementation of best practices, methodologies, and frameworks for sustainable AI system development.
- Technology Stack Selection: Support the evaluation and selection of appropriate tools, technologies, and frameworks tailored to project objectives and future scalability.
- Team Collaboration & Learning: Work alongside experienced AI professionals, contributing to projects while enhancing your knowledge through hands-on involvement.
Requirements:
- Strong understanding of AI concepts, machine learning algorithms, and data structures.
- Familiarity with AI development frameworks (e.g., TensorFlow, PyTorch, Keras).
- Proficiency in programming languages such as Python, Java, or C++.
- Demonstrated interest in system architecture, design thinking, and scalable solutions.
- Up-to-date knowledge of AI trends, tools, and technologies.
- Ability to work independently and collaboratively in a remote team environment
Perks:
- Hands-on experience with real AI projects.
- Mentoring from industry experts.
- A collaborative, innovative and flexible work environment
Compensation:
- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.
After completion of the internship period, there is a chance to get a full-time opportunity as an AI/ML engineer.
Preferred Experience:
- Prior experience in roles such as AI Solution Architect, ML Architect, Data Science Architect, or AI/ML intern.
- Exposure to AI-driven startups or fast-paced technology environments.
- Proven ability to operate in dynamic roles requiring agility, adaptability, and initiative.











