About Us
Neuron7.ai is a rapidly growing AI‑first SaaS company focused on building a category‑defining Service Resolution Intelligence platform. Backed by leading venture capital firms in Silicon Valley and a distinguished group of angel advisors and investors, Neuron7 is widely recognized as a startup to watch.
Our platform enables enterprises to resolve complex operational issues faster by delivering accurate root‑cause analysis and fix recommendations in seconds—leveraging a combination of structured data, unstructured data, and advanced AI agents. Learn more at Neuron7.ai.
Why Join Us
- Work at the frontier of applied AI - LangGraph, LLM, streaming anomaly detection, evidence-based RCA reasoning on real enterprise problems, not toy datasets.
- Both modes of LogIQ (reactive and proactive) are expanding fast; you'll help define how the platform scales to new industries and log ecosystems.
- Your work ships quickly and visibly: demos you build turn into signed contracts; parsers you write run in production within days; tools you create become platform features.
- Engineering depth with customer exposure — you commit to the main repo and influence product direction, while building relationships with some of the world's most complex operations teams.
- Bangalore team with global reach — you'll work closely with the US product and engineering leadership, giving you visibility and mentorship far beyond a typical India engineering role.
The Role:
We are hiring AI Solutions Engineers based in Bangalore who will own the full customer journey from first onboarding call to a live, production LogIQ deployment reactive and proactive. You will work directly with enterprise customers, understand their operational domain, prepare their data, configure the platform, and build compelling demos that show exactly how LogIQ reduces mean-time-to-resolution (MTTR) on their hardest problems.
This is not a support or ticket-handling role. You will write Python, build and register new agent tools, create custom log parsers, configure streaming pipelines, tune LLM prompts, debug async agent failures, and contribute directly to the core platform codebase. You are part engineer, part domain expert, and fully accountable for customer outcomes.
What You'll Do
We are looking for an AI Solutions Engineer with 2–5 years of relevant experience to own the technical customer journey from onboarding and configuration to live production deployments and advanced AI customization.
In this role, you will blend strong software engineering skills, hands‑on AI/LLM experience, and customer‑facing problem solving. You will help enterprises operationalize LogIQ by preparing their data, configuring AI agents, building compelling demos, tuning models, and ensuring successful outcomes at scale.
Key Responsibilities :
1.Customer Onboarding & Platform Configuration
- Provision multi-tenant environments: tenant creation, log file type registration, product family configuration, severity thresholds, and API key management.
2. Streaming Log Ingestion & Proactive Monitoring
- Set up real-time log stream ingestion pipelines — Kafka, Kinesis, Fluentd, syslog-ng, or customer-native agents — into LogIQ's streaming layer.
3. RCA Agent Configuration & Knowledge Enrichment
- Ingest and index customer knowledge articles, historical case resolutions, and equipment documentation into the RCA Agent's retrieval layer (OpenSearch + pgvector).
4. Custom Demo Engineering
- Ingest, clean, and pre-label customer-provided log samples to build compelling, domain-specific demos that speak directly to the customer's operational pain.
5. Agent Tool & Skill Development
- Design, build, and register new LangGraph agent tools as customer use cases demand — e.g., a tool that queries a customer's CMDB, pulls ticket history from ServiceNow, or fetches firmware changelogs from an internal API.
6. Log Parser & Data Connector Development
- Write custom log parsers for proprietary or undocumented equipment formats (Python, plugged into the FastAPI parser registry).
7. Platform Customization & Code Contributions
- Tune LLM system prompts, memory strategies, context windows, and few-shot examples based on observed agent behavior on customer data.
8. Customer Partnership & Knowledge Transfer
- Own the technical relationship for your customer portfolio: onboarding calls, weekly syncs, async Slack/email, and escalation handling.
- Translate customer domain knowledge — telecom alarm semantics, SCADA event codes, IT operations terminology — into LogIQ configuration and agent guidance.
Core Requirements:
- Python Engineering - 2+ years of production Python. Comfortable with asyncio, FastAPI, Pydantic v2, and SQLAlchemy 2.0. Ability to read and extend an unfamiliar codebase quickly.
- LLM & Agent Frameworks - Hands-on experience building or operating LLM-powered agent pipelines — LangChain, LangGraph, CrewAI, AutoGen, or equivalent. Understands state graphs, tool calls, memory, and multi-step reasoning loops.
- Agent Tool Development - Can design, implement, and register new agent tools using the @tool decorator pattern (LangGraph/LangChain). Understands tool allowlists, input/output schemas, and safe integration with existing agent contexts.
- Prompt Engineering - Can systematically diagnose LLM failure modes and improve prompts through controlled iteration. Understands token budgeting, few-shot construction, output format control, and context window management.
- Streaming & Event Systems - Working knowledge of at least one streaming or log-shipping technology — Kafka, Kinesis, Fluentd, Logstash, syslog-ng, or similar. Understands consumer lag, backpressure, and at-least-once delivery semantics.
- Async & Distributed Systems - Understands async task queues (Celery, SQS, Redis), message broker patterns, and how to debug distributed pipeline failures from logs and traces.
- Databases & Search - Solid PostgreSQL fundamentals: schema design, JSONB queries, indexing. Exposure to time-series stores (TimescaleDB) and full-text search (OpenSearch / Elasticsearch) is a plus.
- Cloud & Infrastructure - Comfortable with AWS (S3, SQS, IAM, Kinesis) or Azure equivalents. Docker and container-based local deployments. Familiarity with docker-compose for multi-service dev environments.
- Customer Communication - Strong written and spoken English. Can explain a multi-stage agent failure to a non-technical operations director. Experience in customer-facing technical roles — solutions engineering, implementation, pre-sales, or technical consulting — is a strong plus.
- Education Qualification: B.E. / B.Tech or M.Tech in Computer Science, Electronics, or a related engineering discipline. Equivalent industry experience is fully acceptable.
Nice to Have :
- Direct experience with LangGraph (our production agent runtime) and the Azure OpenAI SDK.
- Familiarity with multi-tenant SaaS architecture and row-level security (RLS) patterns in PostgreSQL.
- Experience building RAG (retrieval-augmented generation) pipelines — chunking, embedding, retrieval strategies, reranking.
- Knowledge of vector databases or pgvector for semantic search over log and knowledge article corpora.
- TypeScript or Angular familiarity
- Domain exposure to telecom (Ciena, Nokia, Ericsson alarms), industrial control systems (SCADA, DCS, PLC events)
- Experience integrating with ITSM tools: ServiceNow, Jira Service Management, PagerDuty, or Salesforce Service Cloud.
- Observability and monitoring experience: Datadog, Grafana, Prometheus , especially for distributed tracing of agent pipelines.
Company Perks & Benefits:
- Competitive salary, equity, and spot bonuses.
- Paid sick leave.
- Comprehensive health insurance.
- Paid parental leave.
- Flexible work arrangements.
Our Commitment to Diversity and Inclusion:
Neuron7.ai is committed to fostering a diverse and inclusive workplace. We ensure equal employment opportunities without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital status, or any other characteristic protected by law.
