Artificial Intelligence Engineer

Esko; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Esko in Bengaluru, India seeks a senior software engineer to design and operate production knowledge platforms. You will architect knowledge representation, build ingestion and retrieval services, and ensure secure, scalable, and auditable systems across multiple customers.

You will work with domain experts and engineers to formalize expert knowledge into testable, provenance-driven components, while enabling validation and escalation when needed.

Qualifications

• 8+ years of software engineering experience in platforms.
• Strong in Python, TypeScript or Java and platform ownership.
• Experience with knowledge, retrieval, or rule systems and formalism choices.
• Hands-on with RAG, information extraction, and validation (JSON Schema/Pydantic).
• Ability to judge applicability, exceptions and ambiguity; know when to escalate.
• Experience building evaluation datasets and documenting decisions.
• Undergrad/Master/PhD in CS/ML/DS/AI or related fields.
• Excellent written and verbal communication with technical and business stakeholders.
• Comfort bridging platform teams and domain engineers.

Responsibilities

• Design the knowledge representation and model constraints to be usable by agents and validators and readable by humans.
• Build and operate platform services for ingesting, curating, retrieving, and versioning knowledge for relevant customers and workflows.
• Define how semantic retrieval, deterministic validation, and human review collaborate, including handling applicability, uncertainty, and escalation.
• Design and implement reusable APIs and tools enabling AI systems and deterministic services to apply, validate, and explain contextual knowledge.
• Build evaluation suites for retrieval quality, applicability, conflict handling, and explanation quality with measurable progress.
• Take end-to-end ownership of major technical areas including security, tenant isolation, reliability, observability, performance, and compatibility.
• Collaborate with domain experts and product engineers to turn informal expertise into structured, testable knowledge with provenance and release practices.

Skills

Python

TypeScript

Java

Platform ownership

Knowledge systems

RAG

JSON Schema

Pydantic

Communication

Evaluation datasets

Domain bridging

Education

Bachelor/Master/PhD in Computer Science / ML / DS / AI

Tools

RDF/OWL

SHACL

Datalog

DMN

production rule engines

policy-as-code

Job description

• Design the knowledge representation: how constraints, transformations, procedures, and guidelines are modelled so that both agents and deterministic validators can use them, and so that humans can read, curate and correct them. 
• Build and operate platform services for ingesting, curating, retrieving, and versioning knowledge, ensuring it is scoped correctly to the relevant customer and workflow context. 
• Define how semantic retrieval, deterministic validation, and human review work together, including how applicability, uncertainty, conflicting evidence, and escalation are handled. 
• Design and implement reusable APIs and tools that allow AI systems and deterministic services to apply, validate, and explain contextual knowledge. 
• Build evaluation suites covering retrieval quality, applicability, conflict and ambiguity handling, and explanation quality, using measurable results as the primary evidence of progress. 
• Take end-to-end ownership of substantial technical areas, including their security, tenant isolation, reliability, observability, performance, and compatibility for consuming teams. 
• Work directly with domain experts and product engineering teams to turn informal expertise into structured, testable knowledge with clear provenance, citation, and release practices. 

What we are looking for

• Strong software engineering experience designing, building, and operating production systems in Python, TypeScript, Java, or a similar language.  
• At least 8 years’ experience in a software engineering role, preferably including ownership of a platform, API or other shared-services product used across multiple internal teams.  
• Experience building knowledge, retrieval, or rule systems that other teams depend on, and the judgement to choose the right formalism for a problem, whether that is a schema, decision table, rules engine, graph, or retrieval. 
• Practical experience with RAG, information extraction, and structured validation (JSON Schema, Pydantic, or equivalent). 
• Sound judgement when reasoning about applicability, exceptions, missing evidence, and ambiguity, including recognizing when a system should decline to answer or require human review. 
• Experience constructing evaluation datasets, and the ability to write clearly about modelling decisions, tradeoffs, and failure modes. 
• Undergraduate, Master’s degree or PhD in Computer Science / Machine Learning / Data Science / Artificial Intelligence, or related disciplines. 
• Comfort operating at the boundary between a platform team and the domain engineering teams that consume it, balancing shared needs and central objectives against individual team priorities and timelines. 
• Excellent written and verbal communication, with the ability to work fluently with both technical and business stakeholders alike. 

Preferred experience

• Semantic and symbolic tooling (RDF/OWL, SHACL, Datalog, DMN, production rule engines, policy-as-code).  
• Agentic systems with tools calling and validation-before-action.  
• Multi-tenant SaaS with strict isolation and audit requirements.  
• Experience in a high-accountability domain such as pharmaceutical or food labelling, and legal technology. 
• Experience in packaging graphics or the wider graphic arts industry