Sr. Software Engineer

AuxoAI is seeking a Senior Applied Scientist to design and deploy structured knowledge systems that enable reliable, schema-grounded AI and agent reasoning.

This role sits at the intersection of large language models, knowledge graphs, semantic architectures, and hybrid retrieval systems. The ideal candidate will build systems that transform unstructured data into structured knowledge representations, enforce semantic constraints, and enable hybrid symbolic–neural reasoning in production environments.

You will play a key role in designing scalable semantic infrastructures that support advanced AI use cases such as GraphRAG pipelines, structured extraction, and agent reasoning workflows.

You will work on problems where existing architectures may not be sufficient and will experiment with new approaches that combine machine learning, knowledge graphs, semantic constraints, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

• Design schema-guided information extraction systems using zero-shot and few-shot structured prompting, constrained decoding approaches such as JSON schema enforcement or grammar-based decoding, and function-calling or tool-driven extraction techniques.
• Develop recursive or multi-stage extraction pipelines capable of handling nested entities, hierarchical structures, and cross-document relationships.
• Build ontology-driven systems using frameworks such as LinkML, OWL, SHACL, or similar schema modeling tools, and implement knowledge representations using RDF triples or labeled property graphs.
• Design and optimize entity resolution algorithms using techniques such as blocking strategies, embedding similarity, and rule-based matching.
• Develop ontology alignment techniques and graph embedding models such as Node2Vec or TransE-style approaches where appropriate.
• Design hybrid retrieval architectures combining dense vector retrieval, sparse retrieval techniques, and graph traversal algorithms such as BFS, DFS, path ranking, and neighborhood expansion.
• Build validation systems that enforce schema conformance, detect semantic inconsistencies, and reduce hallucinated or invalid structured outputs.
• Integrate structured knowledge systems into GraphRAG pipelines, agent planning frameworks, and tool-selection workflows.
• Deliver production-grade semantic systems with clear targets for latency, scalability, reliability, and data integrity.

Requirements

• 5+ years of experience building production AI or machine learning systems.
• Strong experience designing and implementing knowledge graphs or ontology-driven architectures.
• Hands-on experience implementing structured extraction techniques, including grammar-constrained decoding, JSON schema enforcement, or AST-style parsing approaches.
• Experience building entity resolution systems beyond simple embedding similarity methods.
• Experience working with graph query languages such as SPARQL or Cypher and optimizing graph query performance.
• Familiarity with RDF, OWL, or property graph data models and semantic data architectures.
• Strong Python engineering skills, with emphasis on data validation, schema integrity, and system reliability.
• Experience designing hybrid symbolic and neural AI systems.

Nice to Have:

• Experience implementing graph algorithms such as PageRank, community detection, or shortest-path algorithms for reasoning chains.
• Experience building graph-enhanced retrieval systems such as GraphRAG.
• Experience designing compositional semantic extraction pipelines.
• Experience implementing reasoning engines or rule-based inference systems.
• Experience benchmarking and evaluating structural extraction accuracy and consistency.

Roles & Responsibilities

• Design and build ontologies (knowledge models) that organize Dell's business information in a structured way.
• Connect data from different systems so that all information is consistent and easy to understand.
• Create relationships between products, customers, services, and other business data to improve search and AI capabilities.
• Work closely with business teams to understand their requirements and convert them into structured knowledge models.
• Ensure data is organized according to industry standards such as RDF, OWL, and SPARQL.
• Improve enterprise search, analytics, and AI-driven applications by maintaining accurate knowledge structures.
• Collaborate with developers, data engineers, AI teams, and business stakeholders on knowledge management projects.
• Manage and update ontologies as new products, services, and business information are introduced.
• Support knowledge graph and metadata initiatives to improve data quality and consistency.
• Use graph databases and ontology management tools (where applicable) to maintain semantic data models.

Ideal Candidate

• Strong Ontologist Profile with deep semantic (RDF) ontology experience in complex enterprise environments
• Mandatory (Experience 1) – Must have 7+ years of total experience, with 5+ years in semantic (RDF) ontology building/structuring for a complex/large enterprises
• Mandatory (Experience 2) – Must have a strong understanding of content and information management, data structures, and semantic metadata extraction
• Mandatory (Tech skill 1) – Must have strong experience with graph databases, taxonomies, and NLP strategies for optimization
• Mandatory (Tech skill 2) – Must have strong working experience of ontology/TOMS tools such as PoolParty (Semantic Web), TopQuadrant EDG, or GraphDB (Ontotext)
• Mandatory (Tech skill 3) – Must be familiar with W3C industry standards, including SPARQL and OWL.
• Mandatory (Communication) – Must be fluent in English, with strong stakeholder management skills to operate across a complex, multi-team environment.many stakeholders.
• Mandatory (Note) – Must be available to work during US time zones for at least 4 hours per day
• Preferred (Education) – Must have a degree in Computer Science or Library Science, preferably with a minor / concentration / certificate in Information Management or Library Automation
• Preferred (Tech skill 3) – Understanding of content development and search/retrieval tools.

About the Role

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Backend Engineer for a dedicated client engagement building an AI-powered application builder platform.

The backend is the operational core of the product: it manages user projects and sessions, coordinates long-running AI agent workloads, maintains project state, and serves as the integration layer between the frontend, the AI system, and the underlying infrastructure.

The mandatory requirement is hands-on production experience shipping Node.js services, with end-to-end ownership of API design, data modelling, and at least one production system involving background job processing or event-driven patterns.

Responsibilities

API and service development: Design and build REST APIs in Node.js with TypeScript. Cover authentication, session management, input validation, structured error handling, streaming responses (SSE, WebSockets), and rate limiting. Maintain clean API contracts that the frontend and AI system can rely on.

Database design and management: Own PostgreSQL schema design for product domains including user accounts, projects, file trees, session state, and generated artefacts. Write efficient queries, manage migrations, and optimise for read patterns that serve a real-time editor experience.

Caching strategy: Implement and maintain caching with Redis for session data, project state, and frequently read configuration. Design cache invalidation logic that keeps the editor experience consistent without stale reads.

Queue and background job management: Implement and operate background job infrastructure using BullMQ or equivalent. AI agent runs are long-running and stateful; handle retries, failure states, priority queues, and concurrency limits.

AI system integration: Build the integration layer between the backend and the AI agent system. Manage job dispatch, result handling, streaming output to the frontend, and error propagation.

Multi-tenancy and access control: Implement tenant data isolation, RBAC, and resource ownership enforcement across all API surfaces.

Observability and reliability: Instrument services with structured logging, metrics, and tracing. Write defensive code with sensible timeouts, fallback behaviour, and circuit breaking on external dependencies.

Testing and code quality: Write unit and integration tests for the services you ship. Review the work of peers and contribute to shared engineering conventions.

Requirements

• Hands-on production Node.js experience (mandatory) — must have personally shipped at least one feature area end to end in a production Node.js service, owning API design, data modelling, and testing.

• 3 to 5 years of professional backend engineering experience. Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

• Strong Node.js and TypeScript. Production experience with Express, NestJS, or Fastify. Solid with async patterns, streaming, error handling, and building services that run reliably under sustained load.

• PostgreSQL depth. Schema design, query writing, indexing, and migrations on at least one production system.

• Redis and caching. Production experience using Redis for caching and session management. Understands cache invalidation trade-offs.

• Queue and background job systems. Hands-on with BullMQ, RabbitMQ, SQS, or equivalent. Experience managing retries, dead-letter queues, job priority, and concurrency control.

• AWS working knowledge. Comfortable with EC2, S3, RDS, SQS, and IAM. Familiar with Docker and basic deployment and environment management.

• Strong written and spoken English. Able to communicate clearly with engineers across disciplines and write precise technical documentation.

Nice to Have

Experience integrating with AI or LLM services (streaming responses, structured outputs, retry patterns); WebSocket or SSE implementation for real-time features; multi-tenant SaaS product experience; GraphQL; OpenTelemetry instrumentation; prior work on developer tools or editor-style products.

About Sentiaflow

Sentiaflow is an AI engineering and IT services company building production-grade agentic AI systems, sitting at the intersection of LLMs and real business operations — data, APIs, permissions, workflow state, human decisions, security, and measurable outcomes. Our initial domain focus is healthcare, particularly clinical trials, where reliability, traceability, and clear human-decision boundaries matter more than a slick demo.

Job Description

As a Level 1 engineer, you'll implement bounded parts of a production agentic workflow under an Agent Captain or senior engineer, connecting models to application services, tools, data sources, and human approval points.

You will:

• Translate a scoped business workflow into typed inputs, outputs, states, actions, and escalation paths
• Build backend services and tool integrations (Node.js/TypeScript or Python)
• Use LLMs only where model judgment adds value; keep rules, validation, authorization, and workflow control in deterministic code
• Design and validate structured model outputs before they touch downstream systems
• Handle partial data, tool failures, duplicate events, retries, timeouts, rate limits
• Add logging, traces, metrics, and decision records for diagnosability
• Write tests and evaluation cases that check whether the full workflow behaves correctly — not just whether output sounds fluent
• Protect sensitive data; participate in code, design, and release-readiness reviews
• Explain implementation trade-offs clearly to engineers and stakeholders

Success in 6 months: own a bounded workflow module end-to-end, integrate models without letting probabilistic output bypass deterministic controls, produce release-ready evaluation evidence, and diagnose cross-boundary failures with less supervision.

Desired Skills

• Approximately 3–6 years hands-on backend/application engineering experience, with demonstrable hands-on work building agentic systems — not just calling an LLM API from a backend service
• LangGraph (or comparable agent orchestration framework) experience is required — building multi-step, stateful agent workflows with conditional branching, tool-calling loops, and recovery/retry logic, not a single-prompt wrapper
• Deep RAG experience, including:
• Chunking strategy design, embedding model selection, and retrieval evaluation (not just "connected a vector DB")
• Hybrid search (dense + sparse/keyword), re-ranking, and query rewriting/decomposition
• Handling retrieval failure modes: irrelevant context, stale data, contradictory sources, citation/grounding accuracy
• Measuring RAG quality (precision/recall on retrieval, faithfulness/groundedness of generation) — not eyeballing outputs
• Experience designing agent state machines / workflow graphs: tool selection, planning loops, human-in-the-loop interrupts, checkpointing, and state persistence across long-running workflows
• Strong programming in JS/TypeScript (preferred), Python, Java, C#, or Go
• Solid grasp of API design, databases, async processing, auth, testing, deployment
• Comfort reasoning about state, retries, idempotency, concurrency, permissions, audit trails, failure recovery
• Real production debugging experience, not just greenfield builds
• Clear technical communication

We're looking for engineers who've actually built and tuned agentic/RAG systems in production — not those who've only wired together frameworks or prompted an LLM API.

Nice to have: experience with other orchestration frameworks (CrewAI, AutoGen, custom state machines), observability/eval tooling (LangSmith, Langfuse, custom trace pipelines), healthcare or regulated-industry background. Bachelors from IIT or NIT highly preferred.

Job Title : Senior Backend Engineer – Node.js & TypeScript

Experience : 4+ Years

Employment Type : Contract – 3 Months

Location : Pune

Work Mode : On-site

Working Hours : 03:00 PM to 11:00 PM OR 03:00 PM to 12:00 AM

Time Zone : Minimum 4-hour overlap with Eastern Time (ET)

About the Role :

We are looking for a Senior Backend Engineer to design, develop, and scale an AI-led digital platform. The role involves working closely with the Founder/CEO and technical team on architecture, product development, innovation, and end-to-end feature ownership.

Mandatory Skills :

Node.js, TypeScript, REST, GraphQL, PostgreSQL, SQL, Prisma / TypeORM / Sequelize, AWS (ECS, EC2, S3, RDS, Lambda), Airbyte / dbt / Airflow / AWS Glue, Data Warehousing, Event-Driven Architecture, Message Queues, CI/CD, Automated Testing, Backend Architecture, Scalability & Performance.

Key Responsibilities :

• Design and develop scalable backend services using Node.js and TypeScript.
• Build and optimize REST and GraphQL APIs.
• Work with PostgreSQL, SQL, and ORMs such as Prisma / TypeORM / Sequelize.
• Design data pipelines using Airbyte, dbt, Airflow, or AWS Glue.
• Manage and optimize AWS infrastructure including ECS, EC2, S3, RDS, and Lambda.
• Implement CI/CD, automated testing, event-driven architectures, and message queues.
• Optimize API performance, scalability, reliability, and data warehouse solutions.
• Own features end-to-end from design to production.
• Participate in code reviews, on-call support, and production troubleshooting.
• Collaborate with Product, QA, and Engineering teams and mentor junior developers.
• Work closely with the Founder / CEO on technical solutioning and product innovation.

Requirements :

• 4+ years of hands-on Node.js & TypeScript backend development.
• Strong experience with AWS, PostgreSQL, SQL, APIs, and backend architecture.
• Hands-on experience with data pipelines and data warehousing.
• Experience with CI/CD, automated testing, event-driven systems, and message queues.
• Strong problem-solving skills and end-to-end ownership mindset.
• Ability to work independently in a fast-paced environment.
• Good communication and collaboration skills.
• Bachelor's degree in Computer Science, IT, or a related field.

Preferred :

• Terraform / CloudFormation and Infrastructure as Code.
• Docker / Kubernetes and strong DevOps exposure.
• AWS backup / disaster recovery experience.
• Exposure to GCP / Azure.
• Startup / early-stage product development experience.

Data Platform Engineer

Design, automate, and scale our data platform — this is an engineering role, not a traditional "DBA job.

Must-have :

• Data modeling & schema design (from first principles, not just maintenance)
• PostgreSQL (deep, hands-on — partitioning, replication, tuning)
• Any distributed NoSQL store (Cassandra, ScyllaDB, or similar wide-column/distributed DB) (real production experience)
• Python (automation & tooling, not just scripting)
• DevOps & CI/CD (building pipelines, not just using them)
• Terraform (infrastructure-as-code)

You'll:

• Design schemas, partitioning strategies, and lead the Postgres → Cassandra migration end-to-end
• Own PostgreSQL performance, replication, and zero-downtime schema changes
• Build Python-based automation to eliminate repetitive DB work
• Own CI/CD pipelines and Terraform-based infra provisioning
• Drive uptime, DR, monitoring, and incident response
• Own multi-tenant security (RLS, least-privilege access) and data governance

Experience: 4–9 years, data/database/platform engineering in demanding production environments.

Bonus: Kafka/Debezium (CDC), Redis, Flyway/Liquibase, GDPR/DPDP exposure.

4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms 

∙Strong knowledge of data engineering, architecture and data modeling 

∙Experience in platforms like Databricks and Snowflake 

∙Experience on building applications on cloud (AWS or Azure or Google Cloud) 

∙Strong analytical and problem-solving skills 

∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an 

advantage 

∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional 

Programming  

∙Willingness to understand and enhance other people’s code, being able to work in an environment where 

developers will oversee and work on wider components also dealing with older “legacy” code 

∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not 

already mastered at a sufficient level is important 

∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house 

developed frameworks is a must 

∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile 

methodology is an advantage 

∙Prior knowledge of financial products is an advantage 

∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage  

Why This Role Matters

Our backend is what keeps checkout, RTO, and payments fast and reliable at ~$2B GMV across 15,000+ merchants. As an SDE 2 you own services end to end, make the architecture calls that keep them performant, and set the technical bar for the engineers around you. The trade-offs you pick show up directly in merchant conversions and platform reliability - this is a builder's seat with real ownership.

What You'll Own

• Design and build backend services primarily in Node.js/NestJS, with Go for select services, backed by Postgres, Mongo, and Redis.
• Own event-driven flows on Kafka - throughput, ordering, and failure handling.
• Make and document the architecture and trade-off decisions for systems you lead.
• Ship features end to end, dropping into the frontend (React/Svelte) when it's the fastest path.
• Strengthen CI/CD, observability, and deployments on AWS.
• Review code, mentor SDE 1s and AEs, and raise the quality bar on the team.
• Take ambiguous problems and drive them to delivery with minimal hand-holding.

Who You Are

• Strong backend engineer in JavaScript/TypeScript on Node.js/NestJS (our primary stack); working knowledge of Go, or ready to pick it up.
• Solid at data modelling across Postgres and Mongo, and knows when Redis earns its place.
• Has built and scaled event-driven systems (Kafka or equivalent).
• At home on the backend but happy to work across the stack in React/Svelte.
• Thinks in systems - scalability, reliability, maintainability - not just features.
• Has mentored engineers and owns code quality and delivery, not just their own tickets.
• Communicates clearly and does well with ambiguity in a fast-moving team.

🔹 Key Responsibilities

• Design, develop, and deploy production-grade AI/ML and Generative AI solutions

• Work on GEO, AEO, and SGE initiatives to improve visibility across AI-driven search platforms

• Optimize content and digital experiences for conversational queries and LLM-based search

• Develop solutions using LLMs, NLP, embeddings, semantic search, RAG, and vector databases

• Analyze search intent, AI-generated responses, citations, retrieval patterns, and content discoverability

• Build frameworks to measure GEO/AEO strategies and AI-search performance

• Collaborate with Product, Engineering, Content, SEO, Marketing, and Business teams

• Improve solution accuracy, relevance, latency, and user experience

🔹 Mandatory Requirements

✅ 1–4 years of professional experience

✅ Minimum 1 year of hands-on experience in GEO, AEO, or SGE

✅ Experience with prompt engineering, embeddings, vector search, or RAG systems

✅ Understanding of semantic search and entity-based optimization

✅ Exposure to ChatGPT, Google Gemini, or similar LLM platforms

✅ Knowledge of schema, context building, content structuring, and knowledge representation

🎓 Preferred Education

B.Tech, M.Tech, Integrated M.Sc., or MS from a Tier-1 engineering institute such as IIT, NIT, BITS, VIT, DTU, or NSUT.