AI Architect

Join a Global Leader in Workforce Solutions – Net2

Source Inc.

Who We Are
Net2

Source Inc. isn't just another staffing company, we're a powerhouse of innovation, connecting top talent with the right opportunities. Recognized for 300% growth in the past three years, we operate in 34 countries with a global team of 5,500+. Our mission? To bridge the talent gap with precision—Right Talent. Right Time. Right Place. Right Price.

Job Title: AI Consultant (Hands-on)

Location:

Remote
Duration: 06 Months Contract

Job Description

• We are seeking an AI Consultant (hands-on) to support rapid experimentation, proofs of concept (PoCs), and pilot AI solutions that accelerate priority business use cases.

• This role is focused on building quickly, testing ideas, and demonstrating value, leveraging existing internal platforms such as AWS, Databricks, Copilot studio & Power Automate rather than heavy production engineering.

• The ideal candidate is hands-on, pragmatic, and comfortable working in early-stage, exploratory AI efforts where speed and learning matter most.

Key Responsibilities

Rapid PoCs & Pilots:

• Build and iterate on quick-turn AI PoCs, pilots, and demos to validate ideas, workflows, and agent-based experiences. Emphasis is on speed, usability, and learning—not production hardening.

Agentic Experimentation:

• Familiar with agentic harness to configure and test AI agents in a controlled, repeatable way.

• Defining agent roles, prompts, tools, light weight orchestration and simple memory/state handling

• Running structured experiments to test agent behaviors across scenarios

• Iterating on configurations to improve usefulness, reliability, and clarity

• Comparing different agent patterns (e.g., single vs. multi-step flows) and capturing learnings

AWS Usage:

• Use AWS Bedrock & Agentcore to build AI agents with foundation models, agents, and knowledge integrations to support use cases such as summarization, insight generation, content drafting, and workflow assistance.

Databricks-Based Prototyping:

• Leverage Databricks for to build AI agents, lightweight data exploration, preparation, and integration into AI experiments—using notebooks and existing datasets to move fast.

Low-Code / Config-Driven Workflows:

• Favor low-code or configuration-based approaches (prompt templates, reusable configs, simple orchestration patterns) to accelerate development and iteration.

Lightweight Orchestration:

• Connect AI components across tools (e.g., Bedrock ↔ Databricks ↔ APIs, multiple agents within same environment) using simple orchestration patterns sufficient for pilots and demonstrations.

Stakeholder Collaboration:

• Partner closely with product, analytics, and business teams to shape ideas, demo solutions, gather feedback, and refine concepts.

Documentation & Readouts:

• Clearly document PoCs, agent behaviors, findings, and recommendations so successful pilots can be evaluated for future scale-up.

Required Qualifications

• 4–7+ years of experience in AI engineering, data engineering, AI enablement, or applied technology roles.

• Hands-on experience working with AWS (including AWS Bedrock or similar managed AI services).

• Working experience with Databricks (Genie spaces, Playground, etc.)

• Strong Python and SQL skills; comfortable working in notebooks and lightweight scripts.

• Experience building quick prototypes and explaining technical concepts clearly to non-technical stakeholders.

• Ability to work independently and move quickly in a remote, fast-paced environment.

Good to Have (Not Required)

• Familiarity with core AI/ML concepts (e.g., LLMs, embeddings, prompt engineering).

• Exposure to agent-based AI patterns or evaluation frameworks.

• Basic understanding of orchestration or automation tools.

• Prior experience supporting early-stage AI pilots or innovation programs.

Success Metrics

• Delivery of multiple working PoCs or pilots within the first 4–8 weeks.

• Clear stakeholder signal on which ideas are viable and worth further investment.

• Demonstrated acceleration of workflows, insights, or decision-making through AI experimentation.

• Well-documented outcomes and recommendations to support next-phase scaling.

Why Work With Us?
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