Wednesday Solutions
Position: AI Engineer
Location: Pune, Maharashtra
Core Responsibilities Architect:
Choose the right tools, frameworks, and cloud services to meet business goals. Educate: Advise & educate customers on how to use different data engineering, AI/ML algorithms, strategies, and processes from the many options available. Build: Build data pipeline that process, store, integrate and analyze large volumes of data in record time. Create visualisations and insights from the data in order to take informed and data-backed business decisions. Build or leverage AI/ML algorithms to solve real business problems. Communicate: Proactively communicate with your team. Raise blockers, brainstorm solutions, and seek early feedback. Review: Participate in peer reviews to ensure quality deliverables. Tests, Monitoring & Observability: Write tests suites and build automated CI & CD pipelines to deliver more releases and reduce manual effort. Create automated mechanisms to evaluate models with changing variable conditions. Bake in observability and monitoring to ensure outputs are inline with expectations. Learn: Learn from the practices followed by other teams and evangelize your learnings. Showcase: Share your learnings on internal and customer projects via articles, case studies, books, and webinars.Skills Required
- Full Stack Development is a must. Experience with relevant frontend, backend frameworks like React, Next, node/golang/python is a must.
- Experience with cloud providers like AWS/GCP is a must.
- Proficiency in designing, deploying, fine‑tuning, and evaluating LLMs (including RAG and vector‑DB integrations) with built‑in observability and monitoring.
- Hands‑on experience with AI/MLOps workflows and tools (e.g., MLflow, Kubeflow)
- Background in multi‑agent orchestration and multimodal AI systems.
- Experience creating AI workflows using orchestration platforms (e.g., n8n, relay.app) and leveraging a variety of AI tools and plug‑ins (e.g., Byword, Exa, Clay)
- Strong Python expertise with two or more libraries/frameworks (e.g., scikit‑learn, TensorFlow, PyTorch, Keras, NLTK/SpaCy, Hugging Face)
- Proven track record of optimizing models and measuring their business impact (performance metrics & ROI)
- Resilience and adaptability in ambiguous, fast‑moving environments
- Ability to mentor and coach colleagues when needed
Links:
https://in.linkedin.com/compan...