Artificial Intelligence Engineer

We are looking for a Senior AI Engineer (LLMS+ML) to work on a long term freelance mission full time, fully remote for a Client in the Marking Technology Sector.

Start date - Immediate. Immediate Joiners only please

Salary - $2,800 per month (USD)

Location - Fully remote - Please note, this role does not provide sponsorship or sponsorship transfer.

Duration: 12 months+

SUMMARY OF ROLE:

Our Client is evolving into an AI-first platform where every campaign workflow, customer journey, and operational process is augmented by intelligent automation. As part of their major AI roadmap, we are hiring a Senior AI Engineer who is deeply motivated, hands-on, and eager to push boundaries with rapid AI experimentation and productization.

RESPONSIBILITIES:

• Research, prototype, and evaluate AI/ML models for recommendations, matching, forecasting, and content understanding.
• Rapidly validate ideas from the AI Working Group (Tech + Product + Data).
• Build early PoCs for LLM-based assistants (Campaign Advisor, Decision Assistant, internal Knowledge Assistant)
• Implement production-ready AI microservices aligned with our backend architecture (AWS / GCP clouds).
• Integrate models trained on Vertex AI and BigQuery datasets into customer-facing workflows. Define ML pipelines, monitoring, drift detection, and retraining cycles.
• Work closely with the Data team to leverage GCP analytics, build forecasting models, and integrate directly into brand dashboards.
• Build embeddings, content understanding models, and scoring engines for influencers and campaign assets Experiment with predictive monitoring models using our logs.
• Build AI tools for automated code review, test generation, and smart CI/CD Help define MLOps practices, AI ethics, prompt governance, and model versioning - essential for 2026 AI governance layer.

QUALIFICATIONS:

• 5+ years in ML / AI engineering, with strong hands-on experience in: ○ LLMs (Gemini, OpenAI, Claude, Llama, fine-tuning or RAG) ○ ML models for prediction, ranking, recommendations, embeddings ○ Python, FastAPI, or similar backend frameworks.
• Experience deploying ML models in production microservices (REST APIs, containers).
• Solid understanding of MLOps concepts: training pipelines, monitoring, drift, model registries. Experience with GCP (BigQuery, Vertex AI) and/or AWS AI services.
• Ability to move fast and build PoCs within days - not weeks.
• Strong problem-solving, product thinking, and autonomy.

KEY SKILLS:

• Background in analytics: forecasting, attribution modeling, anomaly detection.
• Experience with LangChain, vector DBs, and structured reasoning agents.
• Worked with Data Quality/Data Lineage systems.
• Experience building AI assistants or multi-agent workflows.
• Familiarity with Go-based backend environments or ECS/Fargate deployments.