Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. Wand built the world's first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces.
We're building the infrastructure that lets humans and AI agents operate together safely, transparently, and at scale.
Join Wand in leading the Agentic Shift
Wand is building a high-performing global team who take full ownership of what they build. We lead by example, move fast, make data-aware decisions, and continuously push for more- always with a focus on delivering real value to customers.
You would be joining a world-class team that combines deep research expertise and real-world product execution, with experience spanning Deepmind, Google, Amazon, Miro, Elise AI, IBM and Accern.
We're looking for a Field Solutions Engineer to sit at the intersection of engineering and go-to-market: pairing deep hands-on building with direct customer work to turn Wand's platform into real agent-hours, workflows, and value in production.
You'll work across the lifecycle from early technical validation and pilots through rollout and adoption translating messy business problems into concrete, testable workflows, building believable prototypes, and helping customers scale usage across many use cases.
If you love writing Python, wiring up APIs, and experimenting with LLMs as much as you enjoy talking to customers, this is a chance to shape how enterprises actually adopt the next generation of AI systems.
Build and ship real solutions
Own technical quality: performance, reliability, and auditability of what you ship.
Lead technical validation ('Proof-to-Contract')
Help customers frame clear technical hypotheses: what needs to be proven (accuracy,



coverage, latency, safety) for them to buy.
Design lightweight proofs, benchmarks, and evals that credibly answer, 'Does this actually work for our data and process'
Join customer calls to explain how things work under the hood and handle deep technical questions.
Help design and run onboarding plans: initial workflows, training sessions, office hours, and enablement for power users.
Instrument your solutions for usage and value (DAU/WAU, agent-hours, workflow runs) and use this data to guide iteration.
Contribute Python scripts, API workflows, and reference architectures that show 'the Wand way' to build.
contract review, research copilots, support augmentation) so the next deployment is faster.
Help define and refine internal CE rituals: intake criteria, pilot checklists, and demo/pilot templates.
5+ years in a hands-on technical role such as Sales Engineer, Solutions Architect, Customer/Field Engineer, or Product-adjacent Engineer, working directly with enterprise customers.

Comfortable writing Python in a qualified context (scripts, services, ETL, automation).
Experience integrating with APIs, webhooks, and data sources (files, DBs, SaaS tools).
Experience building with LLMs or applied AI systems:
You've shipped at least one real application, prototype, or internal tool that used an LLM or similar model in production or a serious pilot.
Can listen deeply, translate fuzzy asks into concrete technical work, and push back when a request doesn't make sense.
Bachelor's or Master's in Computer Science, Engineering, or equivalent practical experience.
You care less about 'cool tech' and more about whether the workflow actually saves time, reduces risk, or lets the customer do something genuinely new.
You find the smallest credible thing to build that proves the point and moves the deal or deployment forward.

📌 Solutions Developer (Hybrid) (India)
🏢 Wandai Capital
📍 India