Website:
bodhee.com
Job details:
Technical Leader – Scheduling Algorithms
Location: Bangalore
Experience: 6–7 Years
Function: Engineering / Scheduling Algorithms
Employment Type: Full-time
About Neewee
Neewee is an enterprise software product company building Bodhee, a suite of advanced planning, scheduling, and manufacturing applications designed for complex industrial environments.
Bodhee (www.bodhee.com) is used in manufacturing environments where planning decisions need to take into account real-world constraints such as equipment availability, production sequences, material availability, changeovers, campaign requirements, resource capacities, operating calendars, maintenance events, quality requirements, and continuously changing shop-floor conditions.
Our products include solutions for areas such as:
- Production Scheduling
- Maintenance Scheduling
- Quality Control Scheduling
- Dynamic Schedule Adjustment and Optimization
Bodhee is particularly focused on complex manufacturing environments, including pharmaceutical and vaccine manufacturing, where scheduling decisions can involve a large number of interdependent constraints and operational rules.
The Bodhee technology platform consists of multiple services and technologies including Java, Angular, Python-based scheduling algorithms, optimization engines, PostgreSQL, Kubernetes and cloud infrastructure. The scheduling engine is one of the most critical intellectual-property components of the product.
We are looking for a senior engineer who can take technical and managerial ownership of this area.
What We Are Specifically Looking For
The ideal candidate is someone who can sit with a scheduling domain expert, understand a complex manufacturing scheduling problem, challenge the assumptions, convert the problem into an algorithmic design, guide the team in implementing it in Python, evaluate its performance, understand how it integrates with Java and cloud components, anticipate its impact on existing scheduling scenarios and confidently explain the solution and associated trade-offs to senior leadership.
In short, we are looking for a combination of:
Strong Engineer + Algorithmic Thinker + Architect + Technical Lead + People Leader
rather than a specialist who operates only within one of these areas.
What This Role Is Not
To avoid ambiguity, this role is not primarily:
- A Data Scientist role
- A Machine Learning Engineer role
- A Generative AI Engineer role
- A Python scripting role
- A pure People Manager role
- A Project Manager role
- A DevOps role
It is fundamentally a software engineering and algorithm leadership role responsible for one of the core technology components of the Bodhee platform.
Role Overview
We are looking for a hands-on Technical Lead – Scheduling Algorithms to lead our Scheduling Algorithm engineering team. The role combines technical leadership, algorithm design, Python engineering, architecture, and production systems.
The ideal candidate should be able to translate:
Business Scheduling Problem → Algorithm/Optimization → Python Implementation → Application Architecture → Production Deployment
This is not a Data Science/ML role. We are looking for a strong software engineer with excellent analytical and algorithmic problem-solving skills.
Key Responsibilities
- Lead and mentor the Scheduling Algorithm engineering team.
- Drive technical design, architecture, code reviews and engineering standards.
- Design and implement solutions for complex manufacturing scheduling and optimization problems.
- Translate business requirements and constraints into scalable algorithmic solutions.
- Manage technical debt, engineering priorities, releases and production issues.
- Perform root-cause analysis, debugging and performance optimization.
- Collaborate with Product, Java Backend, UI, QA, DevOps/Cloud, Database and Customer/Implementation teams.
- Communicate technical decisions, risks, trade-offs and solutions to senior leadership.
- Remain hands-on with development and technical problem-solving.
Core Technical Skills – Must Have
Python & Software Engineering
- 6–7+ years of software engineering experience with strong hands-on Python development.
- Strong Python 3.x, OOP, Data Structures & Algorithms.
- Design patterns, modular architecture and clean code principles.
- Type annotations, exception handling, logging and configuration management.
- Unit/integration testing and production debugging.
- REST APIs, JSON and service integration.
- Experience building production-grade/enterprise Python applications.
Algorithms & Optimization
- Strong understanding of computational complexity and algorithmic problem-solving.
- Graphs, search algorithms, heuristics and combinatorial problems.
- Constraint modelling and dependency resolution.
- Optimization and performance-sensitive algorithms.
- Understanding of scheduling/constraint-based problems is highly desirable.
Manufacturing Scheduling – Preferred
- Resource-constrained scheduling.
- Capacity and precedence constraints.
- Equipment/resource availability and calendars.
- Changeovers, setup/cleanup activities.
- Parallel and alternative resources.
- Dynamic scheduling and schedule disruptions.
- Schedule feasibility and optimization.
- Experience with manufacturing scheduling / APS / MES / ERP / production planning is an advantage.
Optimization Technologies – Preferred
- Google OR-Tools / CP-SAT
- Constraint Programming
- Mixed Integer Programming (MIP)
- Mathematical Optimization
- Heuristic / Metaheuristic Optimization
- Operations Research
Architecture & Integration
- Strong understanding of backend/application architecture and distributed systems.
- Ability to understand end-to-end flow:
Angular UI → Java Services → Database → Python Scheduling Engine → Optimization Engine → Results
- Understanding of REST APIs, microservices, asynchronous processing and service-to-service communication.
- Ability to assess the impact of algorithm changes on APIs, databases, application performance, scalability and user workflows.
- Working knowledge of Java enterprise architecture; Java development expertise is not mandatory.
Performance, Cloud & Production
- Experience troubleshooting CPU, memory, execution time and application bottlenecks.
- Understanding of concurrency, parallelism, long-running jobs and timeout handling.
- Experience with Docker and cloud-native applications.
- Exposure to Kubernetes / GCP / AWS / Azure.
- GCP, particularly Cloud Run Jobs, is an advantage.
- Understanding of logging, monitoring and observability.
Engineering Quality & Security
- Strong SDLC understanding: Requirement → Design → Development → Testing → CI/CD → Deployment → Monitoring → RCA.
- Experience with automated, regression, integration and performance testing.
- Ability to test complex algorithms for feasibility, constraints, boundary conditions and unintended impact.
- Understanding of secure coding, API security, input validation, secrets management and dependency security.
Tools & Technologies – Good to Have
Python: PyTest, Pydantic, FastAPI, Poetry/pip, Ruff/Flake8, Black, mypy
Profiling: cProfile, py-spy or similar
Cloud: GCP, AWS, Azure, Docker, Kubernetes
Database: PostgreSQL / relational databases
Architecture: REST APIs, Microservices, Distributed Systems
AI/LLM: LLM APIs, AI Agents, RAG, Tool Calling, AI-assisted Engineering
Leadership & Behavioural Skills
- Strong analytical and structured problem-solving ability.
- Hands-on technical leadership and team mentoring.
- Strong ownership and ability to work with ambiguity.
- Excellent stakeholder and senior-management communication.
- Ability to explain complex technical concepts in simple language.
- Strong collaboration and dependency-management skills.
- Comfortable working in a fast-paced product/start-up environment with changing priorities and customer-critical requirements.
Education
Bachelor’s/Master’s degree in Computer Science, IT, Engineering, Mathematics, Industrial Engineering, Operations Research or a related discipline.
Key Hiring Focus
The strongest candidates will demonstrate a combination of:
Python Engineering + Algorithms + Scheduling/Optimization + Architecture + Technical Leadership
Experience in manufacturing scheduling is an advantage, but candidates with strong algorithmic and software engineering fundamentals who can quickly learn the scheduling domain may also be considered.
Educational Qualification
Bachelor’s or Master’s degree in:
- Computer Science
- Information Technology
- Electronics
- Electrical Engineering
- Mathematics and Computing
- Industrial Engineering
- Operations Research
or another relevant engineering discipline.
Candidates from IITs, IISc, IIITs, NITs, BITS and other reputed engineering institutions are preferred; however, institute pedigree is not a substitute for strong technical capability. Exceptional candidates from other institutions with demonstrated engineering depth and problem-solving ability will be considered.
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